Hypergraph-of-entity A unified representation model for the retrieval of text and knowledge

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

José Devezas (Autor) Outra; Sérgio Nunes (Autor) FEUP

Revista

Título: Open Computer Science

Vol. 9

Páginas: 103-127

Editora: Walter De Gruyter

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 4 Citações

Outras Informações

ID Authenticus: P-00Q-SGY

DOI: 10.1515/comp-2019-0006

Abstract (EN): Modern search is heavily powered by knowledge bases, but users still query using keywords or natural language. As search becomes increasingly dependent on the integration of text and knowledge, novel approaches for a unified representation of combined data present the opportunity to unlock new ranking strategies. We have previously proposed the graph-of-entity as a purely graph-based representation and retrieval model, however this model would scale poorly. We tackle the scalability issue by adapting the model so that it can be represented as a hypergraph. This enables a significant reduction of the number of (hyper)edges, in regard to the number of nodes, while nearly capturing the same amount of information. Moreover, such a higher-order data structure, presents the ability to capture richer types of relations, including nary connections such as synonymy, or subsumption. We present the hypergraph-of-entity as the next step in the graph-of-entity model, where we explore a ranking approach based on biased random walks. We evaluate the approaches using a subset of the INEX 2009 Wikipedia Collection. While performance is still below the state of the art, we were, in part, able to achieve a MAP score similar to TF-IDF and greatly improve indexing efficiency over the graph-of-entity.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 25