By Xinyu Chang Director of Customer Solutions at TigerGraph
Many graph use cases require fuzzy matching, a method used to find similar, but not exactly matching, phrases in a database. Some examples of fuzzy matching include inputting a string of characters, searching records with similar string attribute values, or finding a set of data records that have similar string values. Fuzzy matching is valuable in entity resolution, where data like first and last names needs to be identified and matched. In anti-fraud use cases, fuzzy matching can be used to match unstandardized addresses on credit card applications ...Read More
- Blog https://www.tigergraph.com/blog/minhash-based-fuzzy-match-on-graph/
- Token Bank https://github.com/TigerGraph-DevLabs/minhash-based-fuzzy-match-on-graph/blob/main/TokenBank.cpp
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