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  • What does ZIP stand for (the compression format, not the postal codes)

    - by codymanix
    Does anybody know for what the acronym ZIP stands for which was and is used in programs like PKZIP and GZIP? There is a compression algorithm named Lempel-Ziv-Welch-Algorithm (LZW) maybe the guy named Ziv invented together with other people ZIP? I cannot find anything about it, maybe its not an abbreviation but instead it just means "to zip files" but I think originally there was more about it..

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  • How do you deal with duplicate street suffixes?

    - by Matt
    I have a system where users need to enter addresses. I am trying to limit duplicates of course and something I started noticing was becoming a big problem was some users putting in "Road" and others "Rd", therefore duplicates were creeping in. I looked up the list of USPS street suffix abbreviations but I still have a question which I can't find an answer to. Can I replace all words in a street address with the USPS standard abbreviation? An example would be "123 Forest Hill Road". If I were to replace it with the abbreviations it would then be "123 Frst Hl Rd" or does the "street suffix" that USPS is referring to mean they only want you to make go as far as "123 Forest Hill Rd"?

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  • Split string into sentences based on periods

    - by rookie
    Hi all, I have written this piece of code that splits a string and stores it in a string array:- String[] sSentence = sResult.split("[a-z]\.\s+"); However, I've added the [a-z] because I wanted to deal with some of the abbreviation problem. But then my result shows up as so:- Furthermore when Everett tried to instruct them in basic mathematics they proved unresponsiv I see that I loose the pattern specified in the split function. Its okay for me to loose the period, but loosing the last letter of the word disturbs its meaning. Could some one help me with this and in addition also could someone help me with dealing with abbreviations? Like because I split the string based on periods, I do not want to loose the abbreviations. Thanks in advance

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  • Syntax highlighting Abbreviations

    - by Nimbuz
    I'm using Google prettify for syntax highlighting and I'd like to modify the colors to match my website theme, but I don't understand some of the abbreviations from these: str = string atw kwd = keyword tag = tag com = comment typ = type? atn dec = declaration? lit pun = punctuation? like colons, braces? pln prettyprint

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  • F#: Can't hide a type abbreviation in a signature? Why not?

    - by Nels Beckman
    In F#, I'd like to have what I see as a fairly standard Abstract Datatype: // in ADT.fsi module ADT type my_Type // in ADT.fs module ADT type my_Type = int In other words, code inside the module knows that my_Type is an int, but code outside does not. However, F# seems to have a restriction where type abbreviations specifically cannot be hidden by a signature. This code gives a compiler error, and the restriction is described here. If my_Type were instead a discriminated union, then there is no compiler error. My question is, why the restriction? I seem to remember being able to do this in SML and Ocaml, and furthermore, isn't this a pretty standard thing to do when creating an abstract datatype? Thanks

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  • Predicting Likelihood of Click with Multiple Presentations

    - by Michel Adar
    When using predictive models to predict the likelihood of an ad or a banner to be clicked on it is common to ignore the fact that the same content may have been presented in the past to the same visitor. While the error may be small if the visitors do not often see repeated content, it may be very significant for sites where visitors come repeatedly. This is a well recognized problem that usually gets handled with presentation thresholds – do not present the same content more than 6 times. Observations and measurements of visitor behavior provide evidence that something better is needed. Observations For a specific visitor, during a single session, for a banner in a not too prominent space, the second presentation of the same content is more likely to be clicked on than the first presentation. The difference can be 30% to 100% higher likelihood for the second presentation when compared to the first. That is, for example, if the first presentation has an average click rate of 1%, the second presentation may have an average CTR of between 1.3% and 2%. After the second presentation the CTR stays more or less the same for a few more presentations. The number of presentations in this plateau seems to vary by the location of the content in the page and by the visual attraction of the content. After these few presentations the CTR starts decaying with a curve that is very well approximated by an exponential decay. For example, the 13th presentation may have 90% the likelihood of the 12th, and the 14th has 90% the likelihood of the 13th. The decay constant seems also to depend on the visibility of the content. Modeling Options Now that we know the empirical data, we can propose modeling techniques that will correctly predict the likelihood of a click. Use presentation number as an input to the predictive model Probably the most straight forward approach is to add the presentation number as an input to the predictive model. While this is certainly a simple solution, it carries with it several problems, among them: If the model learns on each case, repeated non-clicks for the same content will reinforce the belief of the model on the non-clicker disproportionately. That is, the weight of a person that does not click for 200 presentations of an offer may be the same as 100 other people that on average click on the second presentation. The effect of the presentation number is not a customer characteristic or a piece of contextual data about the interaction with the customer, but it is contextual data about the content presented. Models tend to underestimate the effect of the presentation number. For these reasons it is not advisable to use this approach when the average number of presentations of the same content to the same person is above 3, or when there are cases of having the presentation number be very large, in the tens or hundreds. Use presentation number as a partitioning attribute to the predictive model In this approach we essentially build a separate predictive model for each presentation number. This approach overcomes all of the problems in the previous approach, nevertheless, it can be applied only when the volume of data is large enough to have these very specific sub-models converge.

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  • NEW 2-Day Instructor Led Course on Oracle Data Mining Now Available!

    - by chberger
    A NEW 2-Day Instructor Led Course on Oracle Data Mining has been developed for customers and anyone wanting to learn more about data mining, predictive analytics and knowledge discovery inside the Oracle Database.  Course Objectives: Explain basic data mining concepts and describe the benefits of predictive analysis Understand primary data mining tasks, and describe the key steps of a data mining process Use the Oracle Data Miner to build,evaluate, and apply multiple data mining models Use Oracle Data Mining's predictions and insights to address many kinds of business problems, including: Predict individual behavior, Predict values, Find co-occurring events Learn how to deploy data mining results for real-time access by end-users Five reasons why you should attend this 2 day Oracle Data Mining Oracle University course. With Oracle Data Mining, a component of the Oracle Advanced Analytics Option, you will learn to gain insight and foresight to: Go beyond simple BI and dashboards about the past. This course will teach you about "data mining" and "predictive analytics", analytical techniques that can provide huge competitive advantage Take advantage of your data and investment in Oracle technology Leverage all the data in your data warehouse, customer data, service data, sales data, customer comments and other unstructured data, point of sale (POS) data, to build and deploy predictive models throughout the enterprise. Learn how to explore and understand your data and find patterns and relationships that were previously hidden Focus on solving strategic challenges to the business, for example, targeting "best customers" with the right offer, identifying product bundles, detecting anomalies and potential fraud, finding natural customer segments and gaining customer insight.

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  • Xpath expression to retrieve oldest/earliest node

    - by gkrogers
    I have an XML snippet, so: <STATES> <STATE> <NAME>Alabama</NAME> <ABBREVIATION>AL</ABBREVIATION> <CAPITAL>Montgomery</CAPITAL> <POPULATION>4661900</POPULATION> <AREA>52419</AREA> <DATEOFSTATEHOOD>14 December 1819</DATEOFSTATEHOOD> </STATE> <STATE> <NAME>Alaska</NAME> <ABBREVIATION>AK</ABBREVIATION> <CAPITAL>Juneau</CAPITAL> <POPULATION>698473</POPULATION> <AREA>663268</AREA> <DATEOFSTATEHOOD>1 January 1959</DATEOFSTATEHOOD> </STATE> <STATE> <NAME>Delaware</NAME> <ABBREVIATION>DE</ABBREVIATION> <CAPITAL>Dover</CAPITAL> <POPULATION>885122</POPULATION> <AREA>2490</AREA> <DATEOFSTATEHOOD>7 December 1787</DATEOFSTATEHOOD> </STATE> </STATES> <etc, etc.> I want to retrieve (for example) the capital of the oldest state (i.e. "Dover"). I have managed to get this far: //STATES/STATE[DATEOFSTATEHOOD='7 December 1787']/CAPITAL/text() but can't figure out how to say 'DATEOFSTATEHOOD={the earliest DATEOFSTATEHOOD}'. Can anybody point me in the right direction, please? SOLUTION: Matt's solution is more or less spot on. I had to reformat the dates (I used YYYYMMDDD) because, as was pointed out, Xpath 1.0 doesn't support the date format I was using. Also, Microsoft's XML library (4.0 and 6.0) returned the whole node list with Matt's expression. Reversing the test fixed that problem, making it return just the earliest node. So: //STATES/STATE[(DATEOFSTATEHOOD < //STATES/STATE/DATEOFSTATEHOOD)]/CAPITAL/text()

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  • Abbreviations override in comments and quoted text

    - by dotancohen
    I have the following handy abbreviation in VIM: iab for for<Space>(<Space>{{<Esc>kA<Left><Left><Left><Left><C-R>=Eatchar('\s')<CR> This nicely replaces for with the following text: for ( ) { } However, I would like this abbreviation to work only in code, not in comments or in single- or double- quoted strings. How might this constraint be accomplished? Note that I usually code in PHP, but often enough I find myself in other C-style languages (C, Java, occasional C#, etc.). Preventing the abbreviation from working in Python would be a nice bonus though I don't mind manually turning it off in Python if that is not an option. Thanks!

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  • Code-Golf: Friendly Number Abbreviator

    - by David Murdoch
    Based on this question: Is there a way to round numbers into a friendly format? THE CHALLENGE - UPDATED! (removed hundreds abbreviation from spec) The shortest code by character count that will abbreviate an integer (no decimals). Code should include the full program. Relevant range is from 0 - 9,223,372,036,854,775,807 (the upper limit for signed 64 bit integer). The number of decimal places for abbreviation will be positive. You will not need to calculate the following: 920535 abbreviated -1 place (which would be something like 0.920535M). Numbers in the tens and hundreds place (0-999) should never be abbreviated (the abbreviation for the number 57 to 1+ decimal places is 5.7dk - it is unneccessary and not friendly). Remember to round half away from zero (23.5 gets rounded to 24). Banker's rounding is verboten. Here are the relevant number abbreviations: h = hundred (102) k = thousand (103) M = million (106) G = billion (109) T = trillion (1012) P = quadrillion (1015) E = quintillion (1018) SAMPLE INPUTS/OUTPUTS (inputs can be passed as separate arguments): First argument will be the integer to abbreviate. The second is the number of decimal places. 12 1 => 12 // tens and hundreds places are never rounded 1500 2 => 1.5k 1500 0 => 2k // look, ma! I round UP at .5 0 2 => 0 1234 0 => 1k 34567 2 => 34.57k 918395 1 => 918.4k 2134124 2 => 2.13M 47475782130 2 => 47.48G 9223372036854775807 3 => 9.223E // ect... . . . Original answer from related question (javascript, does not follow spec): function abbrNum(number, decPlaces) { // 2 decimal places => 100, 3 => 1000, etc decPlaces = Math.pow(10,decPlaces); // Enumerate number abbreviations var abbrev = [ "k", "m", "b", "t" ]; // Go through the array backwards, so we do the largest first for (var i=abbrev.length-1; i>=0; i--) { // Convert array index to "1000", "1000000", etc var size = Math.pow(10,(i+1)*3); // If the number is bigger or equal do the abbreviation if(size <= number) { // Here, we multiply by decPlaces, round, and then divide by decPlaces. // This gives us nice rounding to a particular decimal place. number = Math.round(number*decPlaces/size)/decPlaces; // Add the letter for the abbreviation number += abbrev[i]; // We are done... stop break; } } return number; }

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  • Grouping Collection seperating numeric 5 from String "5"

    - by invertedSpear
    BackGround: I have an advanced data grid. The data provider for this ADG is an ArrayCollection. There is a grouping collection on an ID field of this AC. Example of a couple items within this AC the AC var name is "arcTemplates": (mx.collections::ArrayCollection)#0 filterFunction = (null) length = 69 list = (mx.collections::ArrayList)#1 length = 69 source = (Array)#2 [0] (Object)#3 abbreviation = "sore-throat" insertDate = "11/16/2009" name = "sore throat" templateID = 234 templateType = "New Problem" templateTypeID = 1 [32] (Object)#35 abbreviation = 123 insertDate = "03/08/2010" name = 123 templateID = 297 templateType = "New Problem" templateTypeID = 1 [55] (Object)#58 abbreviation = 1234 insertDate = "11/16/2009" name = 1234 templateID = 227 templateType = "Exam" templateTypeID = 5 [56] (Object)#59 abbreviation = "breast only" insertDate = "03/15/2005" name = "breast exam" templateID = 195 templateType = "Exam" templateTypeID = 5 Example of Flex code leading to the Grouping: <mx:AdvancedDataGrid displayItemsExpanded="true" id="gridTemplates"> <mx:dataProvider> <mx:GroupingCollection id="gc" source="{arcTemplates}"> <mx:Grouping > <mx:GroupingField name="templateTypeID" compareFunction="gcSort"> GC sort function: public function gcSort(a:Object, b:Object):int{ return ObjectUtil.stringCompare(String(a.templateTypeID + a.name).toLowerCase(), String(b.templateTypeID + b.name).toLowerCase()); } Problem: In my AC example there are a few items, items 0, 32 and 56 properly sort and group to their templateTypeID, but item 55 does something weird. It seems to sort/group on the numeric 5 instead of the string "5". Gets stranger. If I change the name property to contain text (so 1234x) it then correctly sorts/groups to the string "5" Question: What is going on here and how do I fix it?

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  • Announcing Two Papers Addressing the RPAS Fusion Client

    - by Oracle Retail Documentation Team
    Oracle Retail has published two documents to My Oracle Support addressing the Retail Predictive Application Server (RPAS) Fusion Client, a web-based rich client developed using the latest Oracle Application Development Framework (ADF). The Fusion Client provides an enhanced user experience for communicating with the RPAS server. Oracle Retail Predictive Application Server Fusion Client Getting Started Guide Doc ID 1492759.1The Retail Predictive Application Server (RPAS) is a configurable platform that provides capabilities such as a multidimensional database structure, batch and online processing, a configurable user interface, a configurable calculation engine, user security, and utility functions such as importing and exporting, all on a highly scalable technical environment that can be deployed on a variety of hardware. This paper addresses typical questions that arise during setting up and deploying the Fusion Client, provides performance recommendations, and highlights the differences between the Classic Client and the Fusion Client. Oracle Retail RPAS Fusion Client Performance Issue Report Doc ID 1493747.1Performance issues can be frustrating for customers, and Oracle Retail will strive to assist you as you attempt to enhance the performance of your systems. To ensure the timeliest processing of your issue, retailers and partners are encouraged to respond as thoroughly as possible to each question in this document, which can be sent back for analysis by logging a Service Request and following typical Customer Support processes. The sections of the document solicit information about the following: Performance Issue Description Performance Issue Details System Configuration Data Application Configuration Data Performance Log Files

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  • php/mysql append state to city

    - by mike
    Hello, Having a hard time figuring out the best way to do this... I have a search function that takes "search terms" and "search location". In the location input, I have an suggestion feature that brings up "city, state abbreviation" but it seems some users just do not use it(or can't) so they end up entering just a city name... I need to append the state abbreviation after the form is submitted. I have a table with all city and state names in the U.S. but the problem is... there are multiple cities with the same name in different states... I would like to add the state abbreviation for the state that the city is most popular for(does that make sense?). For example, if the user enters "Miami" I would like it to become "Miami, FL" as opposed to "Miami, WV"... Any ideas? Thanks!

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  • Is There a Real Advantage to Generic Repository?

    - by Sam
    Was reading through some articles on the advantages of creating Generic Repositories for a new app (example). The idea seems nice because it lets me use the same repository to do several things for several different entity types at once: IRepository repo = new EfRepository(); // Would normally pass through IOC into constructor var c1 = new Country() { Name = "United States", CountryCode = "US" }; var c2 = new Country() { Name = "Canada", CountryCode = "CA" }; var c3 = new Country() { Name = "Mexico", CountryCode = "MX" }; var p1 = new Province() { Country = c1, Name = "Alabama", Abbreviation = "AL" }; var p2 = new Province() { Country = c1, Name = "Alaska", Abbreviation = "AK" }; var p3 = new Province() { Country = c2, Name = "Alberta", Abbreviation = "AB" }; repo.Add<Country>(c1); repo.Add<Country>(c2); repo.Add<Country>(c3); repo.Add<Province>(p1); repo.Add<Province>(p2); repo.Add<Province>(p3); repo.Save(); However, the rest of the implementation of the Repository has a heavy reliance on Linq: IQueryable<T> Query(); IList<T> Find(Expression<Func<T,bool>> predicate); T Get(Expression<Func<T,bool>> predicate); T First(Expression<Func<T,bool>> predicate); //... and so on This repository pattern worked fantastic for Entity Framework, and pretty much offered a 1 to 1 mapping of the methods available on DbContext/DbSet. But given the slow uptake of Linq on other data access technologies outside of Entity Framework, what advantage does this provide over working directly with the DbContext? I attempted to write a PetaPoco version of the Repository, but PetaPoco doesn't support Linq Expressions, which makes creating a generic IRepository interface pretty much useless unless you only use it for the basic GetAll, GetById, Add, Update, Delete, and Save methods and utilize it as a base class. Then you have to create specific repositories with specialized methods to handle all the "where" clauses that I could previously pass in as a predicate. Is the Generic Repository pattern useful for anything outside of Entity Framework? If not, why would someone use it at all instead of working directly with Entity Framework? Edit: Original link doesn't reflect the pattern I was using in my sample code. Here is an (updated link).

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  • Why is SQLite3 using covering indices instead of the indices I created?

    - by Geoff
    I have an extremely large database (contacts has ~3 billion entries, people has ~280 million entries, and the other tables have a negligible number of entries). Most other queries I've run are really fast. However, I've encountered a more complicated query that's really slow. I'm wondering if there's any way to speed this up. First of all, here is my schema: CREATE TABLE activities (id INTEGER PRIMARY KEY, name TEXT NOT NULL); CREATE TABLE contacts ( id INTEGER PRIMARY KEY, person1_id INTEGER NOT NULL, person2_id INTEGER NOT NULL, duration REAL NOT NULL, -- hours activity_id INTEGER NOT NULL -- FOREIGN_KEY(person1_id) REFERENCES people(id), -- FOREIGN_KEY(person2_id) REFERENCES people(id) ); CREATE TABLE people ( id INTEGER PRIMARY KEY, state_id INTEGER NOT NULL, county_id INTEGER NOT NULL, age INTEGER NOT NULL, gender TEXT NOT NULL, -- M or F income INTEGER NOT NULL -- FOREIGN_KEY(state_id) REFERENCES states(id) ); CREATE TABLE states ( id INTEGER PRIMARY KEY, name TEXT NOT NULL, abbreviation TEXT NOT NULL ); CREATE INDEX activities_name_index on activities(name); CREATE INDEX contacts_activity_id_index on contacts(activity_id); CREATE INDEX contacts_duration_index on contacts(duration); CREATE INDEX contacts_person1_id_index on contacts(person1_id); CREATE INDEX contacts_person2_id_index on contacts(person2_id); CREATE INDEX people_age_index on people(age); CREATE INDEX people_county_id_index on people(county_id); CREATE INDEX people_gender_index on people(gender); CREATE INDEX people_income_index on people(income); CREATE INDEX people_state_id_index on people(state_id); CREATE INDEX states_abbreviation_index on states(abbreviation); CREATE INDEX states_name_index on states(name); Note that I've created an index on every column in the database. I don't care about the size of the database; speed is all I care about. Here's an example of a query that, as expected, runs almost instantly: SELECT count(*) FROM people, states WHERE people.state_id=states.id and states.abbreviation='IA'; Here's the troublesome query: SELECT * FROM contacts WHERE rowid IN (SELECT contacts.rowid FROM contacts, people, states WHERE contacts.person1_id=people.id AND people.state_id=states.id AND states.name='Kansas' INTERSECT SELECT contacts.rowid FROM contacts, people, states WHERE contacts.person2_id=people.id AND people.state_id=states.id AND states.name='Missouri'); Now, what I think would happen is that each subquery would use each relevant index I've created to speed this up. However, when I show the query plan, I see this: sqlite> EXPLAIN QUERY PLAN SELECT * FROM contacts WHERE rowid IN (SELECT contacts.rowid FROM contacts, people, states WHERE contacts.person1_id=people.id AND people.state_id=states.id AND states.name='Kansas' INTERSECT SELECT contacts.rowid FROM contacts, people, states WHERE contacts.person2_id=people.id AND people.state_id=states.id AND states.name='Missouri'); 0|0|0|SEARCH TABLE contacts USING INTEGER PRIMARY KEY (rowid=?) (~25 rows) 0|0|0|EXECUTE LIST SUBQUERY 1 2|0|2|SEARCH TABLE states USING COVERING INDEX states_name_index (name=?) (~1 rows) 2|1|1|SEARCH TABLE people USING COVERING INDEX people_state_id_index (state_id=?) (~5569556 rows) 2|2|0|SEARCH TABLE contacts USING COVERING INDEX contacts_person1_id_index (person1_id=?) (~12 rows) 3|0|2|SEARCH TABLE states USING COVERING INDEX states_name_index (name=?) (~1 rows) 3|1|1|SEARCH TABLE people USING COVERING INDEX people_state_id_index (state_id=?) (~5569556 rows) 3|2|0|SEARCH TABLE contacts USING COVERING INDEX contacts_person2_id_index (person2_id=?) (~12 rows) 1|0|0|COMPOUND SUBQUERIES 2 AND 3 USING TEMP B-TREE (INTERSECT) In fact, if I show the query plan for the first query I posted, I get this: sqlite> EXPLAIN QUERY PLAN SELECT count(*) FROM people, states WHERE people.state_id=states.id and states.abbreviation='IA'; 0|0|1|SEARCH TABLE states USING COVERING INDEX states_abbreviation_index (abbreviation=?) (~1 rows) 0|1|0|SEARCH TABLE people USING COVERING INDEX people_state_id_index (state_id=?) (~5569556 rows) Why is SQLite using covering indices instead of the indices I created? Shouldn't the search in the people table be able to happen in log(n) time given state_id which in turn is found in log(n) time?

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  • Fraud and Anomaly Detection using Oracle Data Mining YouTube-like Video

    - by chberger
    I've created and recorded another YouTube-like presentation and "live" demos of Oracle Advanced Analytics Option, this time focusing on Fraud and Anomaly Detection using Oracle Data Mining.  [Note:  It is a large MP4 file that will open and play in place.  The sound quality is weak so you may need to turn up the volume.] Data is your most valuable asset. It represents the entire history of your organization and its interactions with your customers.  Predictive analytics leverages data to discover patterns, relationships and to help you even make informed predictions.   Oracle Data Mining (ODM) automatically discovers relationships hidden in data.  Predictive models and insights discovered with ODM address business problems such as:  predicting customer behavior, detecting fraud, analyzing market baskets, profiling and loyalty.  Oracle Data Mining, part of the Oracle Advanced Analytics (OAA) Option to the Oracle Database EE, embeds 12 high performance data mining algorithms in the SQL kernel of the Oracle Database. This eliminates data movement, delivers scalability and maintains security.  But, how do you find these very important needles or possibly fraudulent transactions and huge haystacks of data? Oracle Data Mining’s 1 Class Support Vector Machine algorithm is specifically designed to identify rare or anomalous records.  Oracle Data Mining's 1-Class SVM anomaly detection algorithm trains on what it believes to be considered “normal” records, build a descriptive and predictive model which can then be used to flags records that, on a multi-dimensional basis, appear to not fit in--or be different.  Combined with clustering techniques to sort transactions into more homogeneous sub-populations for more focused anomaly detection analysis and Oracle Business Intelligence, Enterprise Applications and/or real-time environments to "deploy" fraud detection, Oracle Data Mining delivers a powerful advanced analytical platform for solving important problems.  With OAA/ODM you can find suspicious expense report submissions, flag non-compliant tax submissions, fight fraud in healthcare claims and save huge amounts of money in fraudulent claims  and abuse.   This presentation and several brief demos will show Oracle Data Mining's fraud and anomaly detection capabilities.  

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  • Advanced Analytics Oracle Data Mining - NEW 2-Day Training Course

    - by Mike.Hallett(at)Oracle-BI&EPM
    A NEW 2-Day Oracle University (OU) Instructor Led Course on Oracle Data Mining has been developed for partners and customers to learn more about data mining, predictive analytics and knowledge discovery inside the Oracle Database. Oracle Data Mining, provides data mining algorithms that run native for high performance in-database model building and model deployment. This OU course is a great way to learn the advantages and benefits of "big data analytics"; mining data, building and deploying "predictive analytics" all inside the Oracle Database and to work with OBI. To register for a class, click here, then click on View Schedule to see the latest scheduled classes and/or submit your information expressing interest in attending a class.

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  • Segmentation and Targeting: Your Tools for Personalizing the Online Customer Experience

    - by Christie Flanagan
    In order to deliver the kind of personalized and engaging online experiences that customers expect today, look to segmentation and targeting.  Segmentation is the practice of dividing your site visitors into distinct groups based on shared characteristics or behavior – for example, a segment may consist of site visitors who have visited pages related to certain product type, or they may consist of visitors within the same age group or geographic area.  The idea is that those within a segment are more likely to have common needs, problems or interests that can be served by your business. Targeting is the process by which the most relevant content, whether an article promotion or other piece of content, is delivered to your visitors based on their segment membership. Segmentation and targeting are used to drive greater engagement on your web presence by delivering content to your site visitors that is tailored to their interests, behavior or other attributes.  You may have a number of different goals for your segmentation and targeting efforts: Up-sell or cross-sell to your customers Conduct A/B testing on your offers and creative Offer discounts, promotions or other incentives for the time and duration that you specify Make is easier to find relevant information about products and services Create premium content model There are two different approaches you can take toward segmentation and targeting for you online customer experience initiatives. The first is more of a manual process, in which marketers manage the process of determining which segments to create and which content to target to those segments. The benefit of this approach is that it gives marketers a high level of control over the whole process which works well when you have a thorough understanding of your segments and which content is most likely to serve their needs.  Tools for marketer managed segmentation and targeting are often built right in to your WEM platform, as they are with Oracle WebCenter Sites. The downside is that the more segments and content that you have, the more time consuming and complicated in can be to manage manually.The second approach relies on predictive intelligence to automate the segmentation and targeting process.  This allows optimization of the process to occur in real time. This approach helps reduce the burden of manual segmentation and targeting and can result in new insights into segments that you may never have thought of on your own.  It also provides you with the capability to quickly test new offers and promotions on your site.  Predictive segmentation and targeting can be achieved by using Oracle WebCenter Sites and Oracle Real-Time Decisions together. *****Get a taste for how Oracle WebCenter Sites and Oracle Real-Time Decisions combine to deliver powerful capabilities for predictive segmentation and targeting by watching this on demand webcast introducing Oracle WebCenter Sites 11g or by reading IDC’s take on the latest release of Oracle’s web experience management solution.  Be sure to return to the Oracle WebCenter blog on Thursday for a closer look at how to optimize the online customer experience using these two products together.

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  • Today's $10 Deal from APress - Next-Generation Business Intelligence Software with Silverlight 3

    - by TATWORTH
    Today's $10 deal from Apress is " Next-Generation Business Intelligence Software with Silverlight 3 Business intelligence (BI) software is the code and tools that allow you to view different components of a business using a single visual platform, making comprehending mountains of data easier. BI is everywhere. Applications that include reports, analytics, statistics, and historical and predictive modeling are all examples of BI applications. Currently, we are in the second generation of BI software, called BI 2.0. This generation is focused on writing BI software that is predictive, adaptive, simple, and interactive. Next-Generation Business Intelligence Software with Rich Internet Applications brings you up to speed with the latest BI concepts."

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  • LLBLGen Pro feature highlights: automatic element name construction

    - by FransBouma
    (This post is part of a series of posts about features of the LLBLGen Pro system) One of the things one might take for granted but which has a huge impact on the time spent in an entity modeling environment is the way the system creates names for elements out of the information provided, in short: automatic element name construction. Element names are created in both directions of modeling: database first and model first and the more names the system can create for you without you having to rename them, the better. LLBLGen Pro has a rich, fine grained system for creating element names out of the meta-data available, which I'll describe more in detail below. First the model element related element naming features are highlighted, in the section Automatic model element naming features and after that I'll go more into detail about the relational model element naming features LLBLGen Pro has to offer in the section Automatic relational model element naming features. Automatic model element naming features When working database first, the element names in the model, e.g. entity names, entity field names and so on, are in general determined from the relational model element (e.g. table, table field) they're mapped on, as the model elements are reverse engineered from these relational model elements. It doesn't take rocket science to automatically name an entity Customer if the entity was created after reverse engineering a table named Customer. It gets a little trickier when the entity which was created by reverse engineering a table called TBL_ORDER_LINES has to be named 'OrderLine' automatically. Automatic model element naming also takes into effect with model first development, where some settings are used to provide you with a default name, e.g. in the case of navigator name creation when you create a new relationship. The features below are available to you in the Project Settings. Open Project Settings on a loaded project and navigate to Conventions -> Element Name Construction. Strippers! The above example 'TBL_ORDER_LINES' shows that some parts of the table name might not be needed for name creation, in this case the 'TBL_' prefix. Some 'brilliant' DBAs even add suffixes to table names, fragments you might not want to appear in the entity names. LLBLGen Pro offers you to define both prefix and suffix fragments to strip off of table, view, stored procedure, parameter, table field and view field names. In the example above, the fragment 'TBL_' is a good candidate for such a strip pattern. You can specify more than one pattern for e.g. the table prefix strip pattern, so even a really messy schema can still be used to produce clean names. Underscores Be Gone Another thing you might get rid of are underscores. After all, most naming schemes for entities and their classes use PasCal casing rules and don't allow for underscores to appear. LLBLGen Pro can automatically strip out underscores for you. It's an optional feature, so if you like the underscores, you're not forced to see them go: LLBLGen Pro will leave them alone when ordered to to so. PasCal everywhere... or not, your call LLBLGen Pro can automatically PasCal case names on word breaks. It determines word breaks in a couple of ways: a space marks a word break, an underscore marks a word break and a case difference marks a word break. It will remove spaces in all cases, and based on the underscore removal setting, keep or remove the underscores, and upper-case the first character of a word break fragment, and lower case the rest. Say, we keep the defaults, which is remove underscores and PasCal case always and strip the TBL_ fragment, we get with our example TBL_ORDER_LINES, after stripping TBL_ from the table name two word fragments: ORDER and LINES. The underscores are removed, the first character of each fragment is upper-cased, the rest lower-cased, so this results in OrderLines. Almost there! Pluralization and Singularization In general entity names are singular, like Customer or OrderLine so LLBLGen Pro offers a way to singularize the names. This will convert OrderLines, the result we got after the PasCal casing functionality, into OrderLine, exactly what we're after. Show me the patterns! There are other situations in which you want more flexibility. Say, you have an entity Customer and an entity Order and there's a foreign key constraint defined from the target of Order and the target of Customer. This foreign key constraint results in a 1:n relationship between the entities Customer and Order. A relationship has navigators mapped onto the relationship in both entities the relationship is between. For this particular relationship we'd like to have Customer as navigator in Order and Orders as navigator in Customer, so the relationship becomes Customer.Orders 1:n Order.Customer. To control the naming of these navigators for the various relationship types, LLBLGen Pro defines a set of patterns which allow you, using macros, to define how the auto-created navigator names will look like. For example, if you rather have Customer.OrderCollection, you can do so, by changing the pattern from {$EndEntityName$P} to {$EndEntityName}Collection. The $P directive makes sure the name is pluralized, which is not what you want if you're going for <EntityName>Collection, hence it's removed. When working model first, it's a given you'll create foreign key fields along the way when you define relationships. For example, you've defined two entities: Customer and Order, and they have their fields setup properly. Now you want to define a relationship between them. This will automatically create a foreign key field in the Order entity, which reflects the value of the PK field in Customer. (No worries if you hate the foreign key fields in your classes, on NHibernate and EF these can be hidden in the generated code if you want to). A specific pattern is available for you to direct LLBLGen Pro how to name this foreign key field. For example, if all your entities have Id as PK field, you might want to have a different name than Id as foreign key field. In our Customer - Order example, you might want to have CustomerId instead as foreign key name in Order. The pattern for foreign key fields gives you that freedom. Abbreviations... make sense of OrdNr and friends I already described word breaks in the PasCal casing paragraph, how they're used for the PasCal casing in the constructed name. Word breaks are used for another neat feature LLBLGen Pro has to offer: abbreviation support. Burt, your friendly DBA in the dungeons below the office has a hate-hate relationship with his keyboard: he can't stand it: typing is something he avoids like the plague. This has resulted in tables and fields which have names which are very short, but also very unreadable. Example: our TBL_ORDER_LINES example has a lovely field called ORD_NR. What you would like to see in your fancy new OrderLine entity mapped onto this table is a field called OrderNumber, not a field called OrdNr. What you also like is to not have to rename that field manually. There are better things to do with your time, after all. LLBLGen Pro has you covered. All it takes is to define some abbreviation - full word pairs and during reverse engineering model elements from tables/views, LLBLGen Pro will take care of the rest. For the ORD_NR field, you need two values: ORD as abbreviation and Order as full word, and NR as abbreviation and Number as full word. LLBLGen Pro will now convert every word fragment found with the word breaks which matches an abbreviation to the given full word. They're case sensitive and can be found in the Project Settings: Navigate to Conventions -> Element Name Construction -> Abbreviations. Automatic relational model element naming features Not everyone works database first: it may very well be the case you start from scratch, or have to add additional tables to an existing database. For these situations, it's key you have the flexibility that you can control the created table names and table fields without any work: let the designer create these names based on the entity model you defined and a set of rules. LLBLGen Pro offers several features in this area, which are described in more detail below. These features are found in Project Settings: navigate to Conventions -> Model First Development. Underscores, welcome back! Not every database is case insensitive, and not every organization requires PasCal cased table/field names, some demand all lower or all uppercase names with underscores at word breaks. Say you create an entity model with an entity called OrderLine. You work with Oracle and your organization requires underscores at word breaks: a table created from OrderLine should be called ORDER_LINE. LLBLGen Pro allows you to do that: with a simple checkbox you can order LLBLGen Pro to insert an underscore at each word break for the type of database you're working with: case sensitive or case insensitive. Checking the checkbox Insert underscore at word break case insensitive dbs will let LLBLGen Pro create a table from the entity called Order_Line. Half-way there, as there are still lower case characters there and you need all caps. No worries, see below Casing directives so everyone can sleep well at night For case sensitive databases and case insensitive databases there is one setting for each of them which controls the casing of the name created from a model element (e.g. a table created from an entity definition using the auto-mapping feature). The settings can have the following values: AsProjectElement, AllUpperCase or AllLowerCase. AsProjectElement is the default, and it keeps the casing as-is. In our example, we need to get all upper case characters, so we select AllUpperCase for the setting for case sensitive databases. This will produce the name ORDER_LINE. Sequence naming after a pattern Some databases support sequences, and using model-first development it's key to have sequences, when needed, to be created automatically and if possible using a name which shows where they're used. Say you have an entity Order and you want to have the PK values be created by the database using a sequence. The database you're using supports sequences (e.g. Oracle) and as you want all numeric PK fields to be sequenced, you have enabled this by the setting Auto assign sequences to integer pks. When you're using LLBLGen Pro's auto-map feature, to create new tables and constraints from the model, it will create a new table, ORDER, based on your settings I previously discussed above, with a PK field ID and it also creates a sequence, SEQ_ORDER, which is auto-assigns to the ID field mapping. The name of the sequence is created by using a pattern, defined in the Model First Development setting Sequence pattern, which uses plain text and macros like with the other patterns previously discussed. Grouping and schemas When you start from scratch, and you're working model first, the tables created by LLBLGen Pro will be in a catalog and / or schema created by LLBLGen Pro as well. If you use LLBLGen Pro's grouping feature, which allows you to group entities and other model elements into groups in the project (described in a future blog post), you might want to have that group name reflected in the schema name the targets of the model elements are in. Say you have a model with a group CRM and a group HRM, both with entities unique for these groups, e.g. Employee in HRM, Customer in CRM. When auto-mapping this model to create tables, you might want to have the table created for Employee in the HRM schema but the table created for Customer in the CRM schema. LLBLGen Pro will do just that when you check the setting Set schema name after group name to true (default). This gives you total control over where what is placed in the database from your model. But I want plural table names... and TBL_ prefixes! For now we follow best practices which suggest singular table names and no prefixes/suffixes for names. Of course that won't keep everyone happy, so we're looking into making it possible to have that in a future version. Conclusion LLBLGen Pro offers a variety of options to let the modeling system do as much work for you as possible. Hopefully you enjoyed this little highlight post and that it has given you new insights in the smaller features available to you in LLBLGen Pro, ones you might not have thought off in the first place. Enjoy!

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  • JavaScript variable to ColdFusion variable

    - by Alexander
    I have a tricky one. By means of a <cfoutput query="…"> I list some records in the page from a SQL Server database. By the end of each line viewing I try to add this in to a record in a MySQL database. As you see is simple, because I can use the exact variables from the output query in to my new INSERT INTO statement. BUT: the rsPick.name comes from a database with a different character set and the only way to get it right into my new database is to read it from the web page and not from the value came in the output query. So I read this value with that little JavaScript I made and put it in the myValue variable and then I want ColdFusion to read that variable in order to place it in my SQL statement. <cfoutput query="rsPick"> <tr> <td>#rsPick.ABBREVIATION#</td> <td id="square"> #rsPick.name# </td> <td>#rsPick.Composition#</td> <td> Transaction done... <script type="text/javascript"> var myvalue = document.getElementById("square").innerHTML </script> </td> <cfquery datasource="#Request.Order#"> INSERT INTO products (iniid, abbreviation, clsid, cllid, dfsid, dflid, szsid, szlid, gross, retail, netvaluebc, composition, name) VALUES ( #rsPick.ID#, '#rsPick.ABBREVIATION#', #rsPick.CLSID#, #rsPick.CLLID#, #rsPick.DFSID#, #rsPick.DFLID#, #rsPick.SZSID#, #rsPick.SZLID#, #rsPick.GROSSPRICE#, #rsPick.RETAILPRICE#, #rsPick.NETVALUEBC#, '#rsPick.COMPOSITION#','#MYVALUE#' ) </cfquery> </tr> </cfoutput>

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  • How do I get this sql to linq? Multiple groups

    - by Dwight T
    For a db person, LINQ can be frustrating. I need to convert the following SQL into Linq. SELECT COUNT(o.objectiveid), COUNT(distinct r.ReviewId), l.Abbreviation FROM Objective o JOIN Review r on r.ReviewId = o.ReviewId and r.ReviewPeriodId = 3 and r.IsDeleted = 0 JOIN Position p on p.PositionId = r.EmployeePositionId and p.DivisionId = 2 JOIN Location l on l.LocationId = p.LocationId GROUP BY l.Abbreviation The group by nested example might be the way I have to go, but not sure. Doing one group by I have used the following code: var query = from rev in db.Reviews .Where(r => r.IsDeleted == false && r.ReviewPeriodId == reviewPeriodId) from obj in db.Objectives .Where(o => o.ReviewId == rev.ReviewId && o.IsDeleted == false) from pos in db.Positions .Where(p => rev.EmployeePositionId == p.PositionId && p.IsDeleted == false && p.DivisionId == divisionId ) from loc in db.Locations .Where(l => pos.LocationId == l.LocationId) group loc by loc.Abbreviation into locgroup select new ReportResults { KeyId = 0, Description = locgroup.Key, Count = locgroup.Count() }; return query.ToList(); What is the correct way? Thanks

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  • Oracle Data Mining a Star Schema: Telco Churn Case Study

    - by charlie.berger
    There is a complete and detailed Telco Churn case study "How to" Blog Series just posted by Ari Mozes, ODM Dev. Manager.  In it, Ari provides detailed guidance in how to leverage various strengths of Oracle Data Mining including the ability to: mine Star Schemas and join tables and views together to obtain a complete 360 degree view of a customer combine transactional data e.g. call record detail (CDR) data, etc. define complex data transformation, model build and model deploy analytical methodologies inside the Database  His blog is posted in a multi-part series.  Below are some opening excerpts for the first 3 blog entries.  This is an excellent resource for any novice to skilled data miner who wants to gain competitive advantage by mining their data inside the Oracle Database.  Many thanks Ari! Mining a Star Schema: Telco Churn Case Study (1 of 3) One of the strengths of Oracle Data Mining is the ability to mine star schemas with minimal effort.  Star schemas are commonly used in relational databases, and they often contain rich data with interesting patterns.  While dimension tables may contain interesting demographics, fact tables will often contain user behavior, such as phone usage or purchase patterns.  Both of these aspects - demographics and usage patterns - can provide insight into behavior.Churn is a critical problem in the telecommunications industry, and companies go to great lengths to reduce the churn of their customer base.  One case study1 describes a telecommunications scenario involving understanding, and identification of, churn, where the underlying data is present in a star schema.  That case study is a good example for demonstrating just how natural it is for Oracle Data Mining to analyze a star schema, so it will be used as the basis for this series of posts...... Mining a Star Schema: Telco Churn Case Study (2 of 3) This post will follow the transformation steps as described in the case study, but will use Oracle SQL as the means for preparing data.  Please see the previous post for background material, including links to the case study and to scripts that can be used to replicate the stages in these posts.1) Handling missing values for call data recordsThe CDR_T table records the number of phone minutes used by a customer per month and per call type (tariff).  For example, the table may contain one record corresponding to the number of peak (call type) minutes in January for a specific customer, and another record associated with international calls in March for the same customer.  This table is likely to be fairly dense (most type-month combinations for a given customer will be present) due to the coarse level of aggregation, but there may be some missing values.  Missing entries may occur for a number of reasons: the customer made no calls of a particular type in a particular month, the customer switched providers during the timeframe, or perhaps there is a data entry problem.  In the first situation, the correct interpretation of a missing entry would be to assume that the number of minutes for the type-month combination is zero.  In the other situations, it is not appropriate to assume zero, but rather derive some representative value to replace the missing entries.  The referenced case study takes the latter approach.  The data is segmented by customer and call type, and within a given customer-call type combination, an average number of minutes is computed and used as a replacement value.In SQL, we need to generate additional rows for the missing entries and populate those rows with appropriate values.  To generate the missing rows, Oracle's partition outer join feature is a perfect fit.  select cust_id, cdre.tariff, cdre.month, minsfrom cdr_t cdr partition by (cust_id) right outer join     (select distinct tariff, month from cdr_t) cdre     on (cdr.month = cdre.month and cdr.tariff = cdre.tariff);   ....... Mining a Star Schema: Telco Churn Case Study (3 of 3) Now that the "difficult" work is complete - preparing the data - we can move to building a predictive model to help identify and understand churn.The case study suggests that separate models be built for different customer segments (high, medium, low, and very low value customer groups).  To reduce the data to a single segment, a filter can be applied: create or replace view churn_data_high asselect * from churn_prep where value_band = 'HIGH'; It is simple to take a quick look at the predictive aspects of the data on a univariate basis.  While this does not capture the more complex multi-variate effects as would occur with the full-blown data mining algorithms, it can give a quick feel as to the predictive aspects of the data as well as validate the data preparation steps.  Oracle Data Mining includes a predictive analytics package which enables quick analysis. begin  dbms_predictive_analytics.explain(   'churn_data_high','churn_m6','expl_churn_tab'); end; /select * from expl_churn_tab where rank <= 5 order by rank; ATTRIBUTE_NAME       ATTRIBUTE_SUBNAME EXPLANATORY_VALUE RANK-------------------- ----------------- ----------------- ----------LOS_BAND                                      .069167052          1MINS_PER_TARIFF_MON  PEAK-5                   .034881648          2REV_PER_MON          REV-5                    .034527798          3DROPPED_CALLS                                 .028110322          4MINS_PER_TARIFF_MON  PEAK-4                   .024698149          5From the above results, it is clear that some predictors do contain information to help identify churn (explanatory value > 0).  The strongest uni-variate predictor of churn appears to be the customer's (binned) length of service.  The second strongest churn indicator appears to be the number of peak minutes used in the most recent month.  The subname column contains the interior piece of the DM_NESTED_NUMERICALS column described in the previous post.  By using the object relational approach, many related predictors are included within a single top-level column. .....   NOTE:  These are just EXCERPTS.  Click here to start reading the Oracle Data Mining a Star Schema: Telco Churn Case Study from the beginning.    

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  • Great Blogs About Oracle Solaris 11

    - by Markus Weber
    Now that Oracle Solaris 11 has been released, why not blog about blogs. There is of course a tremendous amount of resource and information available, but valuable insights directly from people actually building the product is priceless. Here's a list of such great blogs. NOTE: If you think we missed some good ones, please let us know in the comments section !  Topic Title Author Top 11 Things My 11 favourite Solaris 11 features Darren Moffat Top 11 Things These are 11 of my favorite things! Mike Gerdts Top 11 Things 11 reason to love Solaris 11     Jim Laurent SysAdmin Resources Solaris 11 Resources for System Administrators Rick Ramsey Overview Oracle Solaris 11: The First Cloud OS Larry Wake Overview What's a "Cloud Operating System"? Harry Foxwell Overview What's New in Oracle Solaris 11 Jeff Victor Try it ! Virtually the fastest way to try Solaris 11 (and Solaris 10 zones) Dave Miner Upgrade Upgrading Solaris 11 Express b151a with support to Solaris 11 Alan Hargreaves IPS The IPS System Repository Tim Foster IPS Building a Solaris 11 repository without network connection Jim Laurent IPS IPS Self-assembly – Part 1: overlays Tim Foster IPS Self assembly – Part 2: multiple packages delivering configuration Tim Foster Security Immutable Zones on Encrypted ZFS Darren Moffat Security User home directory encryption with ZFS Darren Moffat Security Password (PAM) caching for Solaris su - "a la sudo" Darren Moffat Security Completely disabling root logins on Solaris 11 Darren Moffat Security OpenSSL Version in Solaris Darren Moffat Security Exciting Crypto Advances with the T4 processor and Oracle Solaris 11 Valerie Fenwick Performance Critical Threads Optimization Rafael Vanoni Performance SPARC T4-2 Delivers World Record SPECjvm2008 Result with Oracle Solaris 11 BestPerf Blog Performance Recent Benchmarks Using Oracle Solaris 11 BestPerf Blog Predictive Self Healing Introducing SMF Layers Sean Wilcox Predictive Self Healing Oracle Solaris 11 - New Fault Management Features Gavin Maltby Desktop What's new on the Solaris 11 Desktop? Calum Benson Desktop S11 X11: ye olde window system in today's new operating system Alan Coopersmith Desktop Accessible Oracle Solaris 11 - released! Peter Korn

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  • Closed-loop Recommendation Engines: Analyst Insight report on Oracle Real-Time Decisions (RTD)

    - by Mike.Hallett(at)Oracle-BI&EPM
    In November 2011, Helena Schwenk of MWD Advisors, published her analysis on Oracle Real-Time Decisions.  She summarizes as follows: "In contrast to other popular approaches to implementing predictive analytics, RTD focuses on learning from each interaction and using these insights to adjust what is presented, offered or displayed to a customer. Likewise its capabilities for optimising decisions within the context of specific business goals and a report-driven framework for assessing the performance of models and decisions make it a strong contender for organisations that want to continuously improve decision making as part of a customer experience marketing, e-commerce optimisation and operational process efficiency initiative." This is an outstanding report to share with a prospect or client as it goes into great detail about the product and its capabilities.  It also highlights the differences in Oracle's Real-Time Decisions product vs. other closed loop recommendation engines. I encourage you to share this report with your clients and prospects. It can be downloaded directly from here - MWD Advisors Vendor Profile: Oracle Real-Time Decisions. (expires in November 2012) Highlights: "At the core of RTD lies a learning engine that combines business rules and adaptive predictive models to deliver recommendations to operational systems while simultaneously learning from experiences." "While closed-loop recommendation engines are becoming more prevalent... there are a number of features that distinguish RTD: It makes its decisions in the context of the business objectives, such as maximising customer revenue or reducing service costs Its support for operational integration offers organisations some flexibility in how they implement the offering."

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