Fuzzy String Matching with BERT, TF-IDF using PolyFuzz

PolyFuzz performs fuzzy string matching, string grouping, and contains extensive evaluation functions. PolyFuzz is meant to bring fuzzy string matching techniques together within a single framework.

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[soumyaranjansethi]

Amazing suddenly i required this and got your video thank you 🙏

[vinayradhi]

Hi Bhavesh, thank you. fuzzywuzzy or PolyFuzz, which one is more powerful and accurate

[mmeeran]

Hi @bhavesh I tried polyfuzz with 3 models Bert tfidf and editDistance. It took me around 49 mins and colab went offline. I was trying 28k fromlist to match 1400 in tolist. You have any better suggestions?

[madhu]

Had to do something like this.. had to match a name against a large dictionary which has ethnicity of all names. Used Fuzzywuzzy library. Worked well but given the size of the dictionary, it was painfully slow. Not sure if that functionality is available in this lib. Will definitely try this out. Thanks for the video.

[nicolasmontes]

I have a question with the BERT approach. When you try to get the similarity of "apple" and "app" (for example) you need to convert them into a numeric vector (an embedding). But, to get the embedding for "apple" (for example, and the same for "app"), you should see this token in the whole sentence (to get the "contextual embedding"). How they get these embedding if only a word is provided (for example, the token "apple")?

[bbkmujo]

What is this notebook app that you are using?