Graph Algorithms in SQL

Similarity Algorithm (Jaccard)

The Similarity algorithm is used to measure similarities between different sets of nodes or entities in a network. This is done by analyzing the data in each set and giving each set a score. The sets are then compared to each other and given a final score ranging between 0 and 1, where 0 is no match at all, 0.5 is a slight match, and 1 is a perfect match. Timbr’s GA library includes the popular Jaccard Similarity algorithm.

Network of Connected Entities

Similar entities identified for each set

Sample use cases

Recommendations

Recommending products or services based on similar customers purchase history

Marketing

Detecting similar audiences for targeted advertising

Health Care

Predicting patients’ health status based on health data and patient similarity

Text Mining

Identifying similarities between multiple text documents, web pages, etc.

Social Media

Suggesting new relationships based on interests, behavior, etc.

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