Hi All
I have text column in df1 and text column in df2. The length of df2 will be always > length of df1. I want to calculare cosine similarity for every entry in df1[text] against every entry in df2[text] and give a score for every match.
i was facing issues( geeting key errors) when I was trying to match these two columns for similarity . Any help would be greatly appreicated. I have googled a lot and found that in almost all cases people were comparing the first document against rest of documents in the same corpus. here it like comparing every document of corpus 1 with every document on corpus2 .
Thanks
Mahesh
Mahesh Jadhav Did you try using lambda function? Perhaps something like this:
df['cosine_similarity'] = df[['col1', col2']].apply(lambda x1,x2: cosine_sim(x1,x2))
I guess, you can define a function to calculate the similarity between two text strings. And then apply this function to the tuple of every cell of those columns of your dataframe. You should be able to do this between two dataframes as well if you modify the input arguments of your similarity function.
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