Hypergraph-of-Entity: A General Model for Entity-Oriented Search

TL;DR

This paper evaluates the hypergraph-of-entity model for various entity-oriented search tasks, demonstrating its scalability and effectiveness across large datasets like Wikipedia, and proposing it as a universal framework for such searches.

Contribution

It extends the hypergraph-of-entity model to support multiple entity-oriented search tasks and scales it to large collections, providing a general, unified approach.

Findings

Effective for ad hoc entity retrieval and list completion

Scalable to the entire Wikipedia collection

Comparable to state-of-the-art results in INEX tasks

Abstract

The hypergraph-of-entity was conceptually proposed as a general model for entity-oriented search. However, only the performance for ad hoc document retrieval had been assessed. We continue this line of research by also evaluating ad hoc entity retrieval, and entity list completion. We also attempt to scale the model, so that it can support the complete INEX 2009 Wikipedia collection. We do this by indexing the top keywords for each document, reducing complexity by partially lowering the number of nodes and, indirectly, the number of hyperedges linking terms to entities. This enables us to compare the effectiveness of the hypergraph-of-entity with the results obtained by the participants of the INEX tracks for the considered tasks. We find this to be a viable model that is, to our knowledge, the first attempt at a generalization in information retrieval, in particular by supporting a universal ranking function for multiple entity-oriented search tasks.