similarity

given my input data in userid,itemid format: raw: {userid: bytearray,itemid: bytearray} dump raw; (A,1) (A,2) (A,4) (A,5) (B,2) (B,3) (B,5) (C,1) (C,5) grpd = GROUP raw BY userid; dump grpd; (A,{(A,1),(A,2),(A,4),(A,5)}) (B,{(B,2),(B,3),(B,5)}) (C,{(C,1),(C,5)}) I'd like to generate all of the combinations(order not important) of items within each group. I eventually intend on performing jaccard similarity on the items in my group. ideally my the bigrams would be generated and then I'd FLATTEN the output to look like: (A, (1,2)) (A, (1,3)) (A, (1,4)) (A, (2,3)) (A, (2,4)) (A, (3,4)) (B, (1,2))

So, I started with this: http://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance#Ruby Which works great for really small strings. But, my strings can be upwards of 10,000 characters long -- and since the Levenshtein Distance is recursive, this causes a stack too deep error in my Ruby on Rails app. So, is there another, maybe less stack intensive method of finding the similarity between two large strings? Alternatively, I'd need a way to make the stack have much larger size. (I don't think this is the right way to solve the problem, though) Consider a non-recursive

I came across several methods for measuring semantic similarity that use the structure and hierarchy of WordNet, e.g. Jiang and Conrath measure (JNC), Resnik measure(RES), Lin measure (LIN) etc. The way they are measured using NLTK is: sim2=wn.jcn_similarity(entry1,entry2,brown_ic) sim3=entry1.res_similarity(entry2, brown_ic) sim4=entry1.lin_similarity(entry2,brown_ic) If WordNet is the basis of calculating semantic similarity, what is the use of Brown Corpus here? arturomp Take a look at the explanation at the NLTK howto for wordnet. Specifically, the *_ic notation is information content .

I have a table that contains color options for a product. The color options include a hex color code, which is used to generate the UI (HTML). I would like to sort the rows so that the colors in the UI look like a rainbow, instead of the current order that sorts based off of the Name of the color (not very useful). Here is what my query looks like. I get the R G B decimal values from the hex code. I just don't know how to order it. I've looked into color difference algorithms. They seem more useful to compare 2 colors' similarity, not sort. I'm using MySQL: select a.*, (a.c_r + a.c_g + a.c_b)

I'm doing some work that involves document comparison. To do this, I'm analizing each document, and basically counting the number of times some key words appear on each of these documents. For instance: Document 1: Document 2: Book -> 3 Book -> 9 Work -> 0 Work -> 2 Dollar -> 5 Dollar -> 1 City -> 18 City -> 6 So after the counting process, I store all these sequence of numbers in a vector. This sequence of numbers will represent the feature vector for each document. Document 1: [ 3, 0, 5, 18] Document 2: [ 9, 2, 1, 6] The final step would be to normalize the data in a range from [0 1] . But

I came across this term called 'Explicit Semantic Analysis ' which uses Wikipedia as a reference and finds the similarity in documents and categorizes them into classes (correct me if i am wrong). The link i came across is here I wanted to learn more about it. Please help me out with it ! This explicit semantic analysis works on similar lines as semantic similarity . I got hold of this link which provides a clear example of ESA 来源： https://stackoverflow.com/questions/8707624/explicit-semantic-analysis