What are the problems with Jaccard similarity coefficient

List the issues with Jaccard similarity coefficient, What are the problems with Jaccard index, Define Jaccard index, Can we use Jaccard index to find similarity between two documents 

 

Question: List down the issues/problems with Jaccard similarity.   Answer: The Jaccard similarity coefficient, is a statistic used for gauging the similarity and diversity of sample sets. It is calculated as follows; Jaccard (A, B) = |A ∩ B|/|A U B| The number of common members in two sets divided by the total number of members in both the two sets is the Jaccard coefficient. It can be a value between 0 and 1 where 0 indicates no overlap and 1 indicates perfect overlap. Problems with Jaccard It doesn’t consider term frequency (how many times a term occurs in a document). It simply counts the number of terms that are common between two sets. Rare terms in a collection are more informative than frequent terms. Jaccard doesn’t consider this information. Different sized sets with same number of common members also will result in the same Jaccard similarity.

 

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Keywords

List down the issues with Jaccad similarity coefficient

What are the disadvantages of Jaccard similarity index

What Jaccard index value gives perfect overlap?

Can we use Jaccard similarity to measures the closeness between two text documents?