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Search found 293 results on 12 pages for 'phrases'.

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• In need of a semantic thesaurus as a SAS

  - by Roy Peleg

  Hello, I'm currently building a web application. In one of it's key processes the application need to match short phrases to other similar ones available in the DB. The application needs to be able to match the phrase: Looking for a second hand car in good shape To other phrases which basically have the same meaning but use different wording, such as: 2nd hand car in great condition needed or searching for a used car in optimal quality The phrases are length limited (say 250 chars), user generated & unstructured. I'm in need of a service / company / some solution which can help / do these connections for me. Can anyone give any ideas? Thanks, Roy

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• In need of a SaaS solution for semantic thesaurus matching

  - by Roy Peleg

  Hello, I'm currently building a web application. In one of it's key processes the application need to match short phrases to other similar ones available in the DB. The application needs to be able to match the phrase: Looking for a second hand car in good shape To other phrases which basically have the same meaning but use different wording, such as: 2nd hand car in great condition needed or searching for a used car in optimal quality The phrases are length limited (say 250 chars), user generated & unstructured. I'm in need of a service / company / some solution which can help / do these connections for me. Can anyone give any ideas? Thanks, Roy

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• Ngram IDF smoothing

  - by adi92

  I am trying to use IDF scores to find interesting phrases in my pretty huge corpus of documents. I basically need something like Amazon's Statistically Improbable Phrases, i.e. phrases that distinguish a document from all the others The problem that I am running into is that some (3,4)-grams in my data which have super-high idf actually consist of component unigrams and bigrams which have really low idf.. For example, "you've never tried" has a very high idf, while each of the component unigrams have very low idf.. I need to come up with a function that can take in document frequencies of an n-gram and all its component (n-k)-grams and return a more meaningful measure of how much this phrase will distinguish the parent document from the rest. If I were dealing with probabilities, I would try interpolation or backoff models.. I am not sure what assumptions/intuitions those models leverage to perform well, and so how well they would do for IDF scores. Anybody has any better ideas?

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• What are the pro and cons of having localization files vs hard coded variables in source code?

  - by corgrath

  Definitions: Files: Having the localization phrases stored in a physical file that gets read at application start-up and the phrases are stored in the memory to be accessed via util-methods. The phrases are stored in key-value format. One file per language. Variables: The localization texts are stored as hard code variables in the application's source code. The variables are complex data types and depending on the current language, the appropriate phrase is returned. Background: The application is a Java Servlet and the developers use Eclipse as their primary IDE. Some brief pro and cons: Since Eclipse is use, tracking and finding unused localizations are easier when they are saved as variables, compared to having them in a file. However the application's source code becomes bigger and bloated. What are the pro and cons of having localization text in files versus hard coded varibles in source code? What do you do and why?

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• What algorithm would you use to code a parrot?

  - by Phil H

  A parrot learns the most commonly uttered words and phrases in its vicinity so it can repeat them at inappropriate moments. So how would you create a software version? Assuming it has access to a microphone and can record sound at will, how would you code it without requiring infinite resources? The best I can imagine is to divide the stream using silences in the sound, and then use some pattern recognition to encode each one as a list of tokens, storing new ones as you meet them. Hashing the token sequences and counting occurrences in a database, you could build up a picture of the most frequently uttered phrases. But given the huge variety in phrases, how do you prevent this just becoming a huge list? And the sheer number of pairs to match would surely generate lot of false positives from the combinatorial nature of matching. Would you use a neural net, since that's how a real parrot manages it? Or is there another, cleverer way of matching large-scale patterns in analogue data?

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• rails belongs_to sql statement using NULL id

  - by Team Pannous

  When paginating through our Phrase table it takes very long to return the results. In the sql logs we see many sql requests which don't make sense to us: Phrase Load (7.4ms) SELECT "phrases".* FROM "phrases" WHERE "phrases"."id" IS NULL LIMIT 1 User Load (0.4ms) SELECT "users".* FROM "users" WHERE "users"."id" IS NULL LIMIT 1 These add up significantly. Is there a way to prevent querying against null ids? This is the underlying model: class Phrase < ActiveRecord::Base belongs_to :user belongs_to :response, :class_name => "Phrase", :foreign_key => "next_id" end

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• Where would you start if you were trying to solve this PDF classification problem?

  - by burtonic

  We are crawling and downloading lots of companies' PDFs and trying to pick out the ones that are Annual Reports. Such reports can be downloaded from most companies' investor-relations pages. The PDFs are scanned and the database is populated with, among other things, the: Title Contents (full text) Page count Word count Orientation First line Using this data we are checking for the obvious phrases such as: Annual report Financial statement Quarterly report Interim report Then recording the frequency of these phrases and others. So far we have around 350,000 PDFs to scan and a training set of 4,000 documents that have been manually classified as either a report or not. We are experimenting with a number of different approaches including Bayesian classifiers and weighting the different factors available. We are building the classifier in Ruby. My question is: if you were thinking about this problem, where would you start?

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• How to identify a PDF classification problem?

  - by burtonic

  We are crawling and downloading lots of companies' PDFs and trying to pick out the ones that are Annual Reports. Such reports can be downloaded from most companies' investor-relations pages. The PDFs are scanned and the database is populated with, among other things, the: Title Contents (full text) Page count Word count Orientation First line Using this data we are checking for the obvious phrases such as: Annual report Financial statement Quarterly report Interim report Then recording the frequency of these phrases and others. So far we have around 350,000 PDFs to scan and a training set of 4,000 documents that have been manually classified as either a report or not. We are experimenting with a number of different approaches including Bayesian classifiers and weighting the different factors available. We are building the classifier in Ruby. My question is: if you were thinking about this problem, where would you start?

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• Translating with context

  - by translate

  Is there a way I can see the result of my work while I am translating? It is difficult to translate without context. If I could see how my work will appear while I am doing it, translating is much easier. Edit from Oli: I understand this question to be from somebody who is translating an application. Translators often only have a list of phrases to translate without being able to see where those phrases are used in the app. This person wants a way to quickly locate a string inside an application so they can understand the phrase better and provide the best possible translation.

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• Highlight overlapping text in JQuery

  - by Jasie

  I've got this plain HTML: "Many things are in my room: a bed, a desk, and a computer." And these phrases: "things are" "are in my room" "room: a bed" In JQuery, is there some way to loop through the phrase list, and highlight the phrases as they appear in the text, and have the overlap delineated by color, or border, etc? I know there are simple highlighters but that won't do the trick. Maybe something with overlaying opacities? Thanks!

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• AS3: How can I access a movieclip in a different scene?

  - by kentos

  I want to access a MovieClip in another scene than I'm currently in. More specific I want to set a TextField to a certain value from a "preloader"-scene. This is for handling totally dynamic language phrases. Maybe this is the wrong way. I'm loading a XML with language phrases that I want to replace the textfields with. We could do this by altering all MovieClips, but I think this could be a smart solution, if it's possible! :)

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• Map large integer to a phrase

  - by Alexander Gladysh

  I have a large and "unique" integer (actually a SHA1 hash). I want (for no other reason than to have fun) to find an algorithm to convert that SHA1 hash to a (pseudo-)English phrase. The conversion should be reversible (i.e., knowing the algorithm, one must be able to convert the phrase back to SHA1 hash.) The possible usage of the generated phrase: the human readable version of Git commit ID, like a motto for a given program version (which is built from that commit). (As I said, this is "for fun". I don't claim that this is very practical — or be much more readable than the SHA1 itself.) A better algorithm would produce shorter, more natural-looking, more unique phrases. The phrase need not make sense. I would even settle for a whole paragraph of nonsense. (Though quality — englishness — of a paragraph should probably be better than for a mere phrase.) A variation: it is OK if I will be able to work only with a part of hash. Say, first six digits is OK. Possible approach: In the past I've attempted to build a probability table (of words), and generate phrases as Markov chains, seeding the generator (picking branches from probability tree), according to the bits I read from the SHA. This was not very successful, the resulting phrases were too long and ugly. I'm not sure if this was a bug, or the general flaw in the algorithm, since I had to abandon it early enough. Now I'm thinking about attempting to solve the problem once again. Any advice on how to approach this? Do you think Markov chain approach can work here? Something else?

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• Finding Common Byte Sequences in MS SQL TEXT Column

  - by regex

  Hello All, Short Desc: I'm curious to see if I can use SQL Analysis services or some other MS SQL service to mine some data for me that will show commonalities between SQL TEXT fields in a dataset. Long Desc I am looking at a subset of data that consists of about 10,000 rows of TEXT blobs which are used as a notes column in a issue tracking (ticketing) software. I would like to use something out of the box (without having to build something) that might be able to parse through all of the rows and find commonly used byte sequences in the "Notes" column. In other words, I want to find commonly used phrases (two to three word phrases, so 9 - 20 character sections of the TEXT blob). This will help me better determine if associate's notes contain similar phrases (troubleshooting techniques) that we could standardize in our troubleshooting process flow. Closing Note I'd really rather not build an application to do this as my method will probably not be the most efficient way to do it. Hopefully all this makes sense. Please let me know in the comments if anything needs clarification. Thanks in advance for your help.

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• putty pageant - forget keys after period of inactivity

  - by pQd

  in the environment where windows client computers are used to run putty to connect to multiple linux servers i'm considering moving away from password based authentication and using public/private key pairs with pass-phrases. using ssh-agent would be nice, but at the same time i'd like it to 'forget' the pass-phrases after given period of inactivity. it seems that putty's pageant does not provide such feature; what would you suggest as alternative? solutions that i'm considering: patching pageant code [might be tricky, code is probably quite rusty and project - sadly - stagnant] writing small custom application using GetLastInputInfo and killing pageant if the machine was idle for more than let's say 15 minutes [ yes, there'll be separate policy for locking the desktops as well ] using alternative ssh client and ssh agent. any suggestions? thanks!

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• Cowboy Agile?

  - by Robert May

  In a previous post, I outlined the rules of Scrum.  This post details one of those rules. I’ve often heard similar phrases around Scrum that clue me in to someone who doesn’t understand Scrum.  The phrases go something like this: “We don’t do Agile because the idea of letting people just do whatever they want is wrong.  We believe in a more structured approach.” (i.e. Work is Prison, and I’m the Warden!) “I love Agile.  Agile lets us do whatever we want!” (Cowboy Agile?) “We’re Agile, but we use a process that I’ve created.” (Cowboy Agile?) All of those phrases have one thing in common:  The assumption that Agile, and I mean Scrum, lets you do whatever you want.  This is simply not true. Executing Scrum properly requires more dedication, rigor, and diligence than happens in most traditional development methods. Scrum and Waterfall Compared Since Scrum and Waterfall are two of the most commonly used methodologies, a little bit of contrasting and comparing is in order. Waterfall Scrum A project manager defines all tasks and then manages the tasks that team members are working on. The team members define the tasks and estimates of the stories for the current iteration.  Any team member may work on any task in the iteration. Usually only a few milestones that need to be met, the milestones are measured in months, and these milestones are expected to be missed.  Little work is ever done to improve estimates and poor estimators can hide behind high estimates. Stories must be delivered every iteration, milestones are measured in hours, and the team is expected to figure out why their estimates were wrong, even when they were under.  Repeated misses can get the entire team fired. Partially completed work is normal. Partially completed work doesn’t count. Nobody knows the task you’re working on. Everyone knows what you’re working on, whether or not you’re making progress and how much longer you think its going to take, in hours. Little requirement to show working code.  Prototypes are ok. Working code must be shown each iteration.  No smoke and mirrors allowed.  Testing is done in lengthy cycles at the end of development.  Developers aren’t held accountable. Testing is part of the team.  If the testers don’t accept the story as complete, the team can’t count it.  Complete means that the story’s functionality works as designed.  The team can’t have any open defects on the story. Velocity is rarely truly measured and difficult to evaluate. Velocity is integral to the process and can be seen at a glance and everyone in the company knows what it is. A business analyst writes requirements.  Designers mock up screens.  Developers hide behind “I did it just like the spec doc told me to and made the screen exactly like the picture” Developers are expected to collaborate in real time.  If a design is bad or lacks needed details, the developers are required to get it right in the iteration, because all software must be functional.  Designers and Business Analysts are part of the team and must do their work in iterations slightly ahead of the developers. Upper Management is often surprised.  “You told me things were going well two months ago!” Management receives updates at the end of every iteration showing them exactly what the team did and how that compares to what' is remaining in the backlog.  Managers know every iteration what their money is buying. Status meetings are rare or don’t occur.  Email is a primary form of communication. Teams coordinate every single day with each other and use other high bandwidth communication channels to make sure they’re making progress.  Email is used only as a last resort.  Instead, team members stand up, walk to each other, and talk, face to face.  If that’s not possible, they pick up the phone. IF someone asks what happened, its at the end of a lengthy development cycle measured in months, and nobody really knows why it happened. Someone asks what happened every iteration.  The team talks about what happened, and then adapts to make sure that what happened either never happens again or happens every time.   That’s probably enough for now.  As you can see, a lot is required of Scrum teams! One of the key differences in Scrum is that the burden for many activities is shifted to a group of people who share responsibility, instead of a single person having responsibility.  This is a very good thing, since small groups usually come up with better and more insightful work than single individuals.  This shift also results in better velocity.  Team members can take vacations and the rest of the team simply picks up the slack.  With Waterfall, if a key team member takes a vacation, delays can ensue. Scrum requires much more out of every team member and as a result, Scrum teams outperform non-Scrum teams working 60 hour weeks. Recommended Reading Everyone considering Scrum should read Mike Cohn’s excellent book, User Stories Applied. Technorati Tags: Agile,Scrum,Waterfall

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• YouTube SEO: Video Optimization

  - by Mike Stiles

  SEO optimization is still regarded as one of the primary tools in the digital marketing kit. However and wherever a potential customer is conducting a search, brands want their content to surface in the top results. Makes sense. But without a regular flow of good, relevant content, your SEO opportunities run shallow. We know from several studies video is one of the most engaging forms of content, so why not make sure that in addition to being cool, your videos are helping you win the SEO game? Keywords:-Decide what search phrases make the most sense for your video. Don’t dare use phrases that have nothing to do with the content. You’ll make people mad.-Research those keywords to see how competitive they are. Adjust them so there are still lots of people searching for it, but there are not as many links showing up for it.-Search your potential keywords and phrases to see what comes up. It’s amazing how many people forget to do that. Video Title: -Try to start and/or end with your keyword.-When you search on YouTube, visual action words tend to come up as suggested searches. So try to use action words. Video Description: -Lead with a link to your site (include http://). -Don’t stuff this with your keyword. It leads to bad writing and it won’t work anyway. This is where you convince people to watch, so write for humans. Use some showmanship. -At the end, do a call to action (subscribe, see the whole playlist, visit our social channels, etc.) Video Tags:-Don’t over-tag. 5-10 tags per video is plenty. -If you’re compelled to have more than 10, that means you should probably make more videos specifically targeting all those keywords. Find Linking Pals:-45% of videos are discovered on video sites. But 44% are found through links on blogs and sites.-Write a blog about your video’s content, then link to the video in it. -A good site for finding places to guest blog is myblogguest.com-Once you find good linking partners, they’ll link to your future videos (as long as they’re good and you’re returning the favor). Tap the Power of Similar Videos:-Use Video Reply to associate your video with other topic-related videos. That’s when you make a video responding to or referencing a video made by someone else. Content:-Again, build up a portfolio of videos, not just one that goes after 30 keywords.-Create shorter, sequential videos that pull them deeper into the content and closer to a desired final action.-Organize your video topics separately using Playlists. Playlists show up as a whole in search results like individual videos, so optimize playlists the same as you would for a video. Meta Data:-Too much importance is placed on it. It accounts for only 15% of search success.-YouTube reads Captions or Transcripts to determine what a video is about. If you’re not using them, you’re missing out.-You get the SEO benefit of captions and transcripts whether the viewers has them toggled on or not. Promotion:-This accounts for 25% of search success.-Promote the daylights out of your videos using your social channels and digital assets. Don’t assume it’s going to magically get discovered. -You can pay to promote your video. This could surface it on the YouTube home page, YouTube search results, YouTube related videos, and across the Google content network. Community:-Accounts for 10% of search success.-Make sure your YouTube home page is a fun place to spend time. Carefully pick your featured video, and make sure your Playlists are featured. -Participate in discussions so users will see you’re present. The volume of ratings/comments is as important as the number of views when it comes to where you surface on search. Video Sitemaps:-As with a web site, a video sitemap helps Google quickly index your video.-Google wants to know title, description, play page URL, the URL of the thumbnail image you want, and raw video file location.-Sitemaps are xml files you host or dynamically generate on your site. Once you’ve made your sitemap, sign in and submit it using Google webmaster tools. Just as with the broadcast and cable TV channels, putting a video out there is only step one. You also have to make sure everybody knows it’s there so the largest audience possible can see it. Here’s hoping you get great ratings. @mikestiles

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• Algorithm for analyzing text of words

  - by Click Upvote

  I want an algorithm which would create all possible phrases in a block of text. For example, in the text: "My username is click upvote. I have 4k rep on stackoverflow" It would create the following combinations: "My username" "My Username is" "username is click" "is click" "is click upvote" "click upvote" "i have" "i have 4k" "have 4k" .. You get the idea. Basically the point is to get all possible combinations of 'phrases' out of a sentence. Any thoughts for how to best implement this?

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• How to use PredicateBuilder with nested OR conditionals in Linq

  - by tblank

  I've been very happily using PredicateBuilder but until now have only used it for queries with only either concatenated AND statements or OR statements. Now for the first time I need a pair of OR statements nested along with a some AND statements like this: select x from Table1 where a = 1 AND b = 2 AND (z = 1 OR y = 2) Using the documentation from Albahari, I've constructed my expression like this: Expression<Func<TdIncSearchVw, bool>> predicate = PredicateBuilder.True<TdIncSearchVw>(); // for AND Expression<Func<TdIncSearchVw, bool>> innerOrPredicate = PredicateBuilder.False<TdIncSearchVw>(); // for OR innerOrPredicate = innerOrPredicate.Or(i=> i.IncStatusInd.Equals(incStatus)); innerOrPredicate = innerOrPredicate.Or(i=> i.RqmtStatusInd.Equals(incStatus)); predicate = predicate.And(i => i.TmTec.Equals(tecTm)); predicate = predicate.And(i => i.TmsTec.Equals(series)); predicate = predicate.And(i => i.HistoryInd.Equals(historyInd)); predicate.And(innerOrPredicate); var query = repo.GetEnumerable(predicate); This results in SQL that completely ignores the 2 OR phrases. select x from TdIncSearchVw where ((this_."TM_TEC" = :p0 and this_."TMS_TEC" = :p1) and this_."HISTORY_IND" = :p2) If I try using just the OR phrases like: Expression<Func<TdIncSearchVw, bool>> innerOrPredicate = PredicateBuilder.False<TdIncSearchVw>(); // for OR innerOrPredicate = innerOrPredicate.Or(i=> i.IncStatusInd.Equals(incStatus)); innerOrPredicate = innerOrPredicate.Or(i=> i.RqmtStatusInd.Equals(incStatus)); var query = repo.GetEnumerable(innerOrPredicate); I get SQL as expected like: select X from TdIncSearchVw where (IncStatusInd = incStatus OR RqmtStatusInd = incStatus) If I try using just the AND phrases like: predicate = predicate.And(i => i.TmTec.Equals(tecTm)); predicate = predicate.And(i => i.TmsTec.Equals(series)); predicate = predicate.And(i => i.HistoryInd.Equals(historyInd)); var query = repo.GetEnumerable(predicate); I get SQL like: select x from TdIncSearchVw where ((this_."TM_TEC" = :p0 and this_."TMS_TEC" = :p1) and this_."HISTORY_IND" = :p2) which is exactly the same as the first query. It seems like I'm so close it must be something simple that I'm missing. Can anyone see what I'm doing wrong here? Thanks, Terry

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• Query Results Not Expected

  - by E-Madd

  I've been a CF developer for 15 years and I've never run into anything this strange or frustrating. I've pulled my hair out for hours, googled, abstracted, simplified, prayed and done it all in reverse. Can you help me? A cffunction takes one string argument and from that string I build an array of "phrases" to run a query with, attempting to match a location name in my database. For example, the string "the republic of boulder" would produce the array: ["the","republic","of","boulder","the republic","the republic of","the republic of boulder","republic of","republic of boulder","of boulder"]. Another cffunction uses the aforementioned cffunction and runs a cfquery. A query based on the previously given example would be... select locationid, locationname, locationaliasname from vwLocationsWithAlias where LocationName in ('the','the republic','the republic of','republic','republic of','republic of boulder','of','of boulder','boulder') or LocationAliasName in ('the','the republic','the republic of','republic','republic of','republic of boulder','of','of boulder','boulder') This returns 2 records... locationid - locationname - locationalias 99 - 'Boulder' - 'the republic' 68 - 'Boulder' - NULL This is good. Works fine and dandy. HOWEVER... if the string is changed to "the republic", resulting in the phrases array ["the","republic","the republic"] which is then used to produce the query... select locationid, locationname, locationaliasname from vwLocationsWithAlias where LocationName in ('the','the republic','republic') or LocationAliasName in ('the','the republic','republic') This returns 0 records. Say what?! OK, just to make sure I'm not involuntarily HIGH I run that very same query in my SQL console against the same database in the cf datasource. 1 RECORD! locationid - locationname - locationalias 99 - 'Boulder' - 'the republic' I can even hard-code that sql within the same cffunction and get that one result, but never from the dynamically generated SQL. I can get my location phrases from another cffunction of a different name that returns hard-coded array values and those work, but never if the array is dynamically built. I've tried removing cfqueryparams, triple-checking my datatypes, datasource setups, etc., etc., etc. NO DICE WTF!? Is this an obscure bug? Am I losing my mind? I've tried everything I can think of and others (including Ray Camden) can think of. ColdFusion 8 (with all the latest hotfixes) SQL Server 2005 (with all the greatest service packs) Windows 2003 Server (with all the latest updates, service packs and nightly MS voodoo)

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• Python: Find X to Y in a list of strings.

  - by TheLizardKing

  I have a list of maybe a 100 or so elements that is actually an email with each line as an element. The list is slightly variable because lines that have a \n in them are put in a separate element so I can't simply slice using fixed values. I essentially need a variable start and stop phrase (needs to be a partial search as well because one of my start phrases might actually be Total Cost: $13.43 so I would just use Total Cost:.) Same thing with the end phrase. I also do not wish to include the start/stop phrases in the returned list. In summary: email = ['apples','bananas','cats','dogs','elephants','fish','gee'] start = 'ban' stop = 'ele' the magic here new_email = ['cats','dogs'] NOTES While not perfect formatting of the email, it is fairly consistent so there is a slim chance a start/stop phrase will occur more than once. There are also no blank elements.

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• Compare two audio files of beat/tempo and rating in iphone

  - by Senthil Kumar

  Hello, I want to develop iPhone application should have the ability to count the number of phrases that are received when user sing on mic. This application should also have the ability to decipher whether the users phrases are in or out of cadence with a preset beat.When user sing on mic Instrumental music only play. So I have to merge the User Recorded voice with Instrumental music this is one Audio file.Already i have on original Song file.I have to compare both and give the Rating to users. [Note: Instrumental music is without vocal of Original Song file] Can you please help me?. Thanks Vadivelu

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• Joomla 2.5 disable and remove Smart Cache

  - by WooDzu

  I am maintaining a Joomla 2.5 based magazine website with 3-4 new, long articles every day. Smart Search was enabled by default and now I've got a few "finder" tables full of indexed phrases and therms. I wonder if there are any disadvantages if I'd: Disable the Smart Search plugin Remove these 'finder' tables completely Aha, we're using a Search field, which works fine, but I'm not sure what's going to happen if I disable the plugin and remove these tables. Will it then search for phrases in content Joomla tables or simply break w/o missing 'finder' tables Has anyone tried this before?

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• Can anyone recommend a Google SERP tracker?

  - by Haroldo

  I want to track my website's position in Google's search results for around 50 keywords/phrases and I am looking to a nice web service or Windows application to automate this process. Ideally, I want to see pretty Javascript or Flash line graphs for my keywords and their positions. I'm currently free-trialing Raven Tools and Sheer SEO but I am not particularly impressed with either. My budget is up to £25-30/$30-40 per month for a decent rank checker.

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• Using Keyword Analysis to Write Articles and Blogs

  Keyword analysis is a process by which you can discover what search phases are used at search engines by users for find information. Keywords are nothing but search words or phrases entered by users at search engines like Google, Yahoo and Bing. For article, blog and web content writers, keyword research is the most important part of the process.

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• What is Keyword Density?

  One of the phrases that you keep on reading about when you do any type of Search Engine Optimization (SEO) research is keyword density. But is it really?

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