Extracting multi-dimensional relations: a generative model of groups of entities in a corpus

Abstract

Extracting relations among different entities from various data sources has been an important topic in data mining. While many methods focus only on a single type of relations, real world entities maintain relations that contain much richer information. We propose a hierarchical Bayesian model for extracting multi-dimensional relations among entities from a text corpus. Using data from Wikipedia, we show that our model can accurately predict the relevance of an entity given the topic of the document as well as the set of entities that are already mentioned in that document.