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• Structuring Access Control In Hierarchical Object Graph

  - by SB2055

  I have a Folder entity that can be Moderated by users. Folders can contain other folders. So I may have a structure like this: Folder 1 Folder 2 Folder 3 Folder 4 I have to decide how to implement Moderation for this entity. I've come up with two options: Option 1 When the user is given moderation privileges to Folder 1, define a moderator relationship between Folder 1 and User 1. No other relationships are added to the db. To determine if the user can moderate Folder 3, I check and see if User 1 is the moderator of any parent folders. This seems to alleviate some of the complexity of handling updates / moved entities / additions under Folder 1 after the relationship has been defined, and reverting the relationship means I only have to deal with one entity. Option 2 When the user is given moderation privileges to Folder 1, define a new relationship between User 1 and Folder 1, and all child entities down to the grandest of grandchildren when the relationship is created, and if it's ever removed, iterate back down the graph to remove the relationship. If I add something under Folder 2 after this relationship has been made, I just copy all Moderators into the new Entity. But when I need to show only the top-level Folders that a user is Moderating, I need to query all folders that have a parent folder that the user does not moderate, as opposed to option 1, where I just query any items that the user is moderating. Thoughts I think it comes down to determining if users will be querying for all parent items more than they'll be querying child items... if so, then option 1 seems better. But I'm not sure. Is either approach better than the other? Why? Or is there another approach that's better than both? I'm using Entity Framework in case it matters.

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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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• Algorithm for Learning development

  - by user9057

  Hi all, This is a fairly general question. I know a bit of Perl and Python and I am looking to learn programming in more depth so that once I get the hang of it I can start developing applications and then websites. I would like to know of an algorithm (sequence of steps :)) that could describe my approach towards learning programming in general. I have posted small questions on Perl/Python and I have recieved great help from everyone. Note:- I am not in a hurry to learn. I know it takes time and that's fine. Please give any suggestions you think are valid. Also, please don't push me to learn Lisp, Haskell etc - I am a beginner.

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• Labeling algorithm for points

  - by Qwertie

  I need an algorithm to place horizontal text labels for multiple series of points on the screen (basically I need to show timestamps and other information for a history of moving objects on a map; in general there are multiple data points per object). The text labels should appear close to their points--above, below, or on the right side--but should not overlap other points or text labels. Does anyone know an algorithm/heuristic for this?

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• Photo sharing social platform [closed]

  - by user1696497

  I am working on a photo sharing social platform like Flickr, Photobucket. To start off with I have half a million photos as of now. I want to convert all of these into a single format, compression ratio and use it as an original image. I will be storing original image, re-sized image according to layout and a thumbnail. I have started off with ruby, didn't find supporting libraries. I am considering python as it has a good image processing library and instagram is using it. I want some advise about how the image has to be processed while uploading, efficient way of storage whether database or a file system, image compressions, and precautions to be taken. I would be having profile pictures, do I need store them separately or along with the images? If I want to store the images on a file system, which file system should I use and also should I store the url or should I use any intermediate key value store like redis?

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• Algorithm for Learning development

  - by user9057

  This is a fairly general question. I know a bit of Perl and Python and I am looking to learn programming in more depth so that once I get the hang of it I can start developing applications and then websites. I would like to know of an algorithm (sequence of steps :)) that could describe my approach towards learning programming in general. I have posted small questions on Perl/Python and I have recieved great help from everyone. Note:- I am not in a hurry to learn. I know it takes time and that's fine. Please give any suggestions you think are valid. Also, please don't push me to learn Lisp, Haskell etc - I am a beginner.

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• Resolving equivalence relations

  - by Luca Cerone

  I am writing a function to label the connected component in an image (I know there are several libraries outside, I just wanted to play with the algorithm). To do this I label the connected regions with different labels and create an equivalence table that contain information on the labels belonging to the same connected component. As an example if my equivalence table (vector of vector) looks something like: 1: 1,3 2: 2,3 3: 1,2,3 4: 4 It means that in the image there are 2 different regions, one made of elements that are labelled 1,2,3 and an other made of elements labelled 4. What is an easy and efficient way to resolve the equivalences and end up with something that looks like: 1: 1,2,3 2: 4 that I can use to "merge" the different connected regions belonging to the same connected component? Thanks a lot for the help!

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• Looking for an algorithm to connect dots - shortest route

  - by e4ch

  I have written a program to solve a special puzzle, but now I'm kind of stuck at the following problem: I have about 3200 points/nodes/dots. Each of these points is connected to a few other points (usually 2-5, theoretical limit is 1-26). I have exactly one starting point and about 30 exit points (probably all of the exit points are connected to each other). Many of these 3200 points are probably not connected to neither start nor end point in any way, like a separate net, but all points are connected to at least one other point. I need to find the shortest number of hops to go from entry to exit. There is no distance between the points (unlike the road or train routing problem), just the number of hops counts. I need to find all solutions with the shortest number of hops, and not just one solution, but all. And potentially also solutions with one more hop etc. I expect to have a solution with about 30-50 hops to go from start to exit. I already tried: 1) randomly trying possibilities and just starting over when the count was bigger than a previous solution. I got first solution with 3500 hops, then it got down to about 97 after some minutes, but looking at the solutions I saw problems like unnecessary loops and stuff, so I tried to optimize a bit (like not going back where it came from etc.). More optimizations are possible, but this random thing doesn't find all best solutions or takes too long. 2) Recursively run through all ways from start (chess-problem-like) and breaking the try when it reached a previous point. This was looping at about a length of 120 nodes, so it tries chains that are (probably) by far too long. If we calculate 4 possibilities and 120 nodes, we're reaching 1.7E72 possibilities, which is not possible to calculate through. This is called Depth-first search (DFS) as I found out in the meantime. Maybe I should try Breadth-first search by adding some queue? The connections between the points are actually moves you can make in the game and the points are how the game looks like after you made the move. What would be the algorithm to use for this problem? I'm using C#.NET, but the language shouldn't matter.

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• How to quickly search through a very large list of strings / records on a database

  - by Giorgio

  I have the following problem: I have a database containing more than 2 million records. Each record has a string field X and I want to display a list of records for which field X contains a certain string. Each record is about 500 bytes in size. To make it more concrete: in the GUI of my application I have a text field where I can enter a string. Above the text field I have a table displaying the (first N, e.g. 100) records that match the string in the text field. When I type or delete one character in the text field, the table content must be updated on the fly. I wonder if there is an efficient way of doing this using appropriate index structures and / or caching. As explained above, I only want to display the first N items that match the query. Therefore, for N small enough, it should not be a big issue loading the matching items from the database. Besides, caching items in main memory can make retrieval faster. I think the main problem is how to find the matching items quickly, given the pattern string. Can I rely on some DBMS facilities, or do I have to build some in-memory index myself? Any ideas? EDIT I have run a first experiment. I have split the records into different text files (at most 200 records per file) and put the files in different directories (I used the content of one data field to determine the directory tree). I end up with about 50000 files in about 40000 directories. I have then run Lucene to index the files. Searching for a string with the Lucene demo program is pretty fast. Splitting and indexing took a few minutes: this is totally acceptable for me because it is a static data set that I want to query. The next step is to integrate Lucene in the main program and use the hits returned by Lucene to load the relevant records into main memory.

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• Algorithm for determining grid based on variably sized "blocks"?

  - by Lite Byte

  I'm trying to convert a set of "blocks" in to a grid-like layout. The blocks have a width of either 25%, 33%, 50%, 66%, or 75% of their container and each row of the grid should try to fit as many blocks as possible, up to a total width of 100%. I've discovered that trying to do this while leaving no remaining blocks in the original set is very hard. Eventually, I think my solution will be to upgrade/downgrade various block sizes (based on their priority or something) so they all fit in to a row. Either case, before I do that, I thought I'd check if someone has some code (or a paper) demonstrating a solution to this problem already? And bonus points if the solution incorporates varying block heights in to its calculations :) Thanks!

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• How would you tackle a pattern-finding program?

  - by Neil

  Just to be clear, I don't think this should be question better suited for stackoverflow.com simply because there's not a single answer but a wide range of possible solutions, making this question far more subjective in nature. I was curious how you guys would tackle a pattern-finding program, which is to say I'd do the following operations: I enter in some input. Program predicts my next input based on all previous inputs. Rinse. Repeat. Since the amount of input I could provide is so varied, including empty strings, conventional means such as switches or regular expressions are out, since it would require you to have an inkling of information about what to expect. I was thinking about some form of genetic algorithm, yet even then I don't have a clue as to how to approach a problem of this caliber. I think some feedback mechanism would be necessary as well as to let the program know how close it was. Anyone had to do a similar type program before?

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• Algorithm to generate N random numbers between A and B which sum up to X

  - by Shaamaan

  This problem seemed like something which should be solvable with but a few lines of code. Unfortunately, once I actually started to write the thing, I've realized it's not as simple as it sounds. What I need is a set of X random numbers, each of which is between A and B and they all add up to X. The exact variables for the problem I'm facing seem to be even simpler: I need 5 numbers, between -1 and 1 (note: these are decimal numbers), which add up to 1. My initial "few lines of code, should be easy" approach was to randomize 4 numbers between -1 and 1 (which is simple enough), and then make the last one 1-(sum of previous numbers). This quickly proved wrong, as the last number could just as well be larger than 1 or smaller than -1. What would be the best way to approach this problem? PS. Just for reference: I'm using C#, but I don't think it matters. I'm actually having trouble creating a good enough solution for the problem in my head.

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• Tiling Problem Solutions for Various Size "Dominoes"

  - by user67081

  I've got an interesting tiling problem, I have a large square image (size 128k so 131072 squares) with dimensons 256x512... I want to fill this image with certain grain types (a 1x1 tile, a 1x2 strip, a 2x1 strip, and 2x2 square) and have no overlap, no holes, and no extension past the image boundary. Given some probability for each of these grain types, a list of the number required to be placed is generated for each. Obviously an iterative/brute force method doesn't work well here if we just randomly place the pieces, instead a certain algorithm is required. 1) all 2x2 square grains are randomly placed until exhaustion. 2) 1x2 and 2x1 grains are randomly placed alternatively until exhaustion 3) the remaining 1x1 tiles are placed to fill in all holes. It turns out this algorithm works pretty well for some cases and has no problem filling the entire image, however as you might guess, increasing the probability (and thus number) of 1x2 and 2x1 grains eventually causes the placement to stall (since there are too many holes created by the strips and not all them can be placed). My approach to this solution has been as follows: 1) Create a mini-image of size 8x8 or 16x16. 2) Fill this image randomly and following the algorithm specified above so that the desired probability of the entire image is realized in the mini-image. 3) Create N of these mini-images and then randomly successively place them in the large image. Unfortunately there are some downfalls to this simplification. 1) given the small size of the mini-images, nailing an exact probability for the entire image is not possible. Example if I want p(2x1)=P(1x2)=0.4, the mini image may only give 0.41 as the closes probability. 2) The mini-images create a pseudo boundary where no overlaps occur which isn't really descriptive of the model this is being used for. 3) There is only a fixed number of mini-images so i'm not sure how random this really is. I'm really just looking to brainstorm about possible solutions to this. My main concern is really to nail down closer probabilities, now one might suggest I just increase the mini-image size. Well I have, and it turns out that in certain cases(p(1x2)=p(2x1)=0.5) the mini-image 16x16 isn't even iteratively solvable.. So it's pretty obvious how difficult it is to randomly solve this for anything greater than 8x8 sizes.. So I'd love to hear some ideas. Thanks

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• Developing a search algorithm

  - by Richart Bremer

  I want to create a basic search engine, and I want you to give me some ideas how to filter out the best results for my visitors. I have three fields regarding a product the user can search in: Title Category Description I came up with these ideas and I ask you to either competently criticize them or add to them. If the search term occurs in all three fields it should be among the first results. If it is in two of the fields it is below the results of 1. Combine the amount of occurences and output a value in per cent. For instance if in all fields together the term clock appeared 50 times and in all fields together there are 200 words, then the per cent value is 50/200*100 = 25%. Another product entry amounts to say 20% so product one having 25% is listed before product two having 20%.

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• Even distribution through a chain of resources

  - by ClosetGeek

  I'm working on an algorithm which routes tasks through a chain of distributed resources based on a hash (or random number). For example, say you have 10 gateways into a service which distribute tasks to 1000 handlers through 100 queues. 10,000 connected clients are expected to be connected to gateways at any given time (numbers are very general to keep it simple). Thats 10,000 clients 10 gateways (producers) 100 queues 1000 workers/handlers (consumers) The flow of each task is client-gateway-queue-worker Each client will have it's own hash/number which is used to route each task from the client to the same worker each time, with each task going through the same gateway and queue each time. Yet the algorithm handles distribution evenly, meaning each gateway, queue, and worker will have an even workload. My question is what exactly would this be called? Does such a thing already exist? This started off as a DHT, but I realized that DHTs can't do exactly what I need, so I started from scratch.

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• Improving python code

  - by cobie

  I just answered the question on project euler about finding circular primes below 1 million using python. My solution is below. I was able to reduce the running time of the solution from 9 seconds to about 3 seconds. I would like to see what else can be done to the code to reduce its running time further. This is strictly for educational purposes and for fun. import math import time def getPrimes(n): """returns set of all primes below n""" non_primes = [j for j in range(4, n, 2)] # 2 covers all even numbers for i in range(3, n, 2): non_primes.extend([j for j in range(i*2, n, i)]) return set([i for i in range(2, n)]) - set(non_primes) def getCircularPrimes(n): primes = getPrimes(n) is_circ = [] for prime in primes: prime_str = str(prime) iter_count = len(prime_str) - 1 rotated_num = [] while iter_count > 0: prime_str = prime_str[1:] + prime_str[:1] rotated_num.append(int(prime_str)) iter_count -= 1 if primes >= set(rotated_num): is_circ.append(prime) return len(is_circ)

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• Using replacement to get possible outcomes to then search through HUGE amount of data

  - by Samuel Cambridge

  I have a database table holding 40 million records (table A). Each record has a string a user can search for. I also have a table with a list of character replacements (table B) i.e. i = Y, I = 1 etc. I need to be able to take the string a user is searching for, iterate through each letter and create an array of every possible outcome (the users string, then each outcome with alternative letters used). I need to check for alternatives on both lower and uppercase letters in the word A search string can be no longer than 10 characters long. I'm using PHP and a MySQL database. Does anyone have any thoughts / articles / guidance on doing this in an efficient way?

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• A look at an example of anti-spam algorithm

  - by pragmaticCamel

  What is a good approach to an anti-spam algorithm for a website similar to reddit? Their anti-spam algorithm seems awfully broken (banning on words in the title and doing a horrible job for that matter). Considering a post spam because it has the word 'spam' in the title is really not a wise choice. Anyway, how can one approach such problem ? Are there any tools that help in such cases? Also, what are the /technical/ reasons behind reddit's choice not using reCAPTCHA on every post submission? It seems like a much better solution than what they have right now. Since reddit is basically a community-driven website why not give such power to the communities' trusted members?

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• Logic - Time measurement

  - by user73384

  To measure the following for tasks- Last execution time and maximum execution time for each task. CPU load/time consumed by each task over a defined period informed by application at run time. Maximum CPU load consumed by each task. Tasks have following characteristics- First task runs as background – Event information for entering only Second task - periodic – Event information for entering and exiting from task Third task is interrupt , can start any time – no information available from this task Forth task highest priority interrupt , can start any time – Event information for entering and exiting from task Should use least possible execution time and memory. 32bit increment timer available for time counting. Lets prepare and discuss the logic, It’s OK to have limitations …! Questions on understanding problem statement are welcome

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• What's a good algorithm for a random, uneven distribution of a fixed amount of a resource?

  - by NickC

  Problem I have X, a positive integer, of some resource, R. There are N potential targets. I want to distribute all of R to the N targets in some "interesting" way. "Interesting" means: Some targets may not get any R. It should rarely be near even (with a majority of target getting near X/N of the resource). There should be at least a small chance of one target getting all of R. Bad solutions The naive approach would be to pick a random target and give one R to it and repeat X times. This would result in too even of an approach. The next idea is to pick a random number between 1 and X and give it to a random target. This results in too large of a number (at least X/2 on average) being given to one target. Question This algorithm will be used frequently and I want the distribution to be interesting and uneven so that the surprise doesn't wear off for users. Is there a good algorithm for something in between these two approaches, that fits the definition of interesting above?

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• Matching users based on a series of questions

  - by SeanWM

  I'm trying to figure out a way to match users based on specific personality traits. Each trait will have its own category. I figure in my user table I'll add a column for each category: id name cat1 cat2 cat3 1 Sean ? ? ? 2 Other ? ? ? Let's say I ask each user 3 questions in each category. For each question, you can answer one of the following: No, Maybe, Yes How would I calculate one number based off the answers in those 3 questions that would hold a value I can compare other users to? I was thinking having some sort of weight. Like: No -> 0 Maybe -> 1 Yes -> 2 Then doing some sort of meaningful calculation. I want to end up with something like this so I can query the users and find who matches close: id name cat1 cat2 cat3 1 Sean 4 5 1 2 Other 1 2 5 In the situation above, the users don't really match. I'd want to match with someone with a +1 or -1 of my score in each category. I'm not a math guy so I'm just looking for some ideas to get me started.

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• Efficient way to find unique elements in a vector compared against multiple vectors

  - by SyncMaster

  I am trying find the number of unique elements in a vector compared against multiple vectors using C++. Suppose I have, v1: 5, 8, 13, 16, 20 v2: 2, 4, 6, 8 v3: 20 v4: 1, 2, 3, 4, 5, 6, 7 v5: 1, 3, 5, 7, 11, 13, 15 The number of unique elements in v1 is 1 (i.e. number 16). I tried two approaches. Added vectors v2,v3,v4 and v5 into a vector of vector. For each element in v1, checked if the element is present in any of the other vectors. Combined all the vectors v2,v3,v4 and v5 using merge sort into a single vector and compared it against v1 to find the unique elements. Note: sample_vector = v1 and all_vectors_merged contains v2,v3,v4,v5 //Method 1 unsigned int compute_unique_elements_1(vector<unsigned int> sample_vector,vector<vector<unsigned int> > all_vectors_merged) { unsigned int duplicate = 0; for (unsigned int i = 0; i < sample_vector.size(); i++) { for (unsigned int j = 0; j < all_vectors_merged.size(); j++) { if (std::find(all_vectors_merged.at(j).begin(), all_vectors_merged.at(j).end(), sample_vector.at(i)) != all_vectors_merged.at(j).end()) { duplicate++; } } } return sample_vector.size()-duplicate; } // Method 2 unsigned int compute_unique_elements_2(vector<unsigned int> sample_vector, vector<unsigned int> all_vectors_merged) { unsigned int unique = 0; unsigned int i = 0, j = 0; while (i < sample_vector.size() && j < all_vectors_merged.size()) { if (sample_vector.at(i) > all_vectors_merged.at(j)) { j++; } else if (sample_vector.at(i) < all_vectors_merged.at(j)) { i++; unique ++; } else { i++; j++; } } if (i < sample_vector.size()) { unique += sample_vector.size() - i; } return unique; } Of these two techniques, I see that Method 2 gives faster results. 1) Method 1: Is there a more efficient way to find the elements than running std::find on all the vectors for all the elements in v1. 2) Method 2: Extra overhead in comparing vectors v2,v3,v4,v5 and sorting them. How can I do this in a better way?

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• What is a good algorithm to distribute items with specific requirements?

  - by user66160

  I have to programmatically distribute a set of items to some entities, but there are rules both on the items and on the entities like so: Item one: 100 units, only entities from Foo Item two: 200 units, no restrictions Item three: 100 units, only entities that have Bar Entity one: Only items that have Baz Entity one hundred: No items that have Fubar I only need to be pointed in the right direction, I'll research and learn the suggested methods.

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• What is an efficient algorithm for randomly assigning a pool of objects to a parent using specific rules

  - by maple_shaft

  I need some expert answers to help me determine the most efficient algorithm in this scenario. Consider the following data structures: type B { A parent; } type A { set<B> children; integer minimumChildrenAllowed; integer maximumChildrenAllowed; } I have a situation where I need to fetch all the orphan children (there could be hundreds of thousands of these) and assign them RANDOMLY to A type parents based on the following rules. At the end of the job, there should be no orphans left At the end of the job, no object A should have less children than its predesignated minimum. At the end of the job, no object A should have more children than its predesignated maximum. If we run out of A objects then we should create a new A with default values for minimum and maximum and assign remaining orphans to these objects. The distribution of children should be as evenly distributed as possible. There may already be some children assigned to A before the job starts. I was toying with how to do this but I am afraid that I would just end up looping across the parents sorted from smallest to largest, and then grab an orphan for each parent. I was wondering if there is a more efficient way to handle this?

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• High-level strategy for distinguishing a regular string from invalid JSON (ie. JSON-like string detection)

  - by Jonline

  Disclaimer On Absence of Code: I have no code to post because I haven't started writing; was looking for more theoretical guidance as I doubt I'll have trouble coding it but am pretty befuddled on what approach(es) would yield best results. I'm not seeking any code, either, though; just direction. Dilemma I'm toying with adding a "magic method"-style feature to a UI I'm building for a client, and it would require intelligently detecting whether or not a string was meant to be JSON as against a simple string. I had considered these general ideas: Look for a sort of arbitrarily-determined acceptable ratio of the frequency of JSON-like syntax (ie. regex to find strings separated by colons; look for colons between curly-braces, etc.) to the number of quote-encapsulated strings + nulls, bools and ints/floats. But the smaller the data set, the more fickle this would get look for key identifiers like opening and closing curly braces... not sure if there even are more easy identifiers, and this doesn't appeal anyway because it's so prescriptive about the kinds of mistakes it could find try incrementally parsing chunks, as those between curly braces, and seeing what proportion of these fractional statements turn out to be valid JSON; this seems like it would suffer less than (1) from smaller datasets, but would probably be much more processing-intensive, and very susceptible to a missing or inverted brace Just curious if the computational folks or algorithm pros out there had any approaches in mind that my semantics-oriented brain might have missed. PS: It occurs to me that natural language processing, about which I am totally ignorant, might be a cool approach; but, if NLP is a good strategy here, it sort of doesn't matter because I have zero experience with it and don't have time to learn & then implement/ this feature isn't worth it to the client.

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