tf-idf

问题 I am trying to work out how to improve the scoring of solr search results. My application needs to take the score from the solr results and display a number of “stars” depending on how good the result(s) are to the query. 5 Stars = almost/exact down to 0 stars meaning not matching the search very well, e.g. only one element hits. However I am getting scores from 1.4 to 0.8660254 both are returning results that I would give 5 stars to. What I need to do is somehow turn these results in to a

问题 I searched a lot for understanding this but I am not able to. I understand that by default TfidfVectorizer will apply l2 normalization on term frequency. This article explain the equation of it. I am using TfidfVectorizer on my text written in Gujarati language. Following is details of output about it: My two documents are: ખુબ વખાણ કરે છે ખુબ વધારે છે The code I am using is: vectorizer = TfidfVectorizer(tokenizer=tokenize_words, sublinear_tf=True, use_idf=True, smooth_idf=False) Here,

问题 I need to compare documents stored in a DB and come up with a similarity score between 0 and 1. The method I need to use has to be very simple. Implementing a vanilla version of n-grams (where it possible to define how many grams to use), along with a simple implementation of tf-idf and Cosine similarity. Is there any program that can do this? Or should I start writing this from scratch? 回答1: Check out NLTK package: http://www.nltk.org it has everything what you need For the cosine_similarity

问题 I have created Term Frequency using HashingTF in Spark. I have got the term frequencies using tf.transform for each word. But the results are showing in this format. [<hashIndexofHashBucketofWord1>,<hashIndexofHashBucketofWord2> ...] ,[termFrequencyofWord1, termFrequencyOfWord2 ....] eg: (1048576,[105,3116],[1.0,2.0]) I am able to get the index in hash bucket, using tf.indexOf(\"word\") . But, how can I get the word using the index? 回答1: Well, you can't. Since hashing is non-injective there

问题 i have built an index in Lucene. I want without specifying a query, just to get a score (cosine similarity or another distance?) between two documents in the index. For example i am getting from previously opened IndexReader ir the documents with ids 2 and 4. Document d1 = ir.document(2); Document d2 = ir.document(4); How can i get the cosine similarity between these two documents? Thank you 回答1: When indexing, there's an option to store term frequency vectors. During runtime, look up the