This module includes a number of functions to perform knowledge discovery in graph embeddings.
Functions provided include
discover_facts which will generate candidate statements using one of several
defined strategies and return triples that perform well when evaluated against corruptions,
will perform link-based cluster analysis on a knowledge graph,
find_duplicates which will find duplicate entities
in a graph based on their embeddings, and
query_topn which when given two elements of a triple will return
the top_n results of all possible completions ordered by predicted score.
||Discover new facts from an existing knowledge graph.|
||Perform link-based cluster analysis on a knowledge graph.|
||Find duplicate entities, relations or triples in a graph based on their embeddings.|
||Queries the model with two elements of a triple and returns the top_n results of all possible completions ordered by score predicted by the model.|
||Return the nearest neighbors of entities.|