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.
Similar entities identified for each set
Sample use cases
Recommending products or services based on similar customers purchase history
Detecting similar audiences for targeted advertising
Predicting patients’ health status based on health data and patient similarity
Identifying similarities between multiple text documents, web pages, etc.
Suggesting new relationships based on interests, behavior, etc.