Graph-of-Entity: A Model for Combined Data Representation and Retrieval

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

José Devezas (Author) Other; Carla Teixeira Lopes (Author) FEUP; Sérgio Nunes (Author) FEUP

Conference proceedings International

Title: OpenAccess Series in Informatics

Pages: 1:1-1:14

8th Symposium on Languages, Applications and Technologies, SLATE 2019

27 June 2019 through 28 June 2019

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00Q-ZR4

DOI: 10.4230/oasics.slate.2019.1

Abstract (EN): Managing large volumes of digital documents along with the information they contain, or are associated with, can be challenging. As systems become more intelligent, it increasingly makes sense to power retrieval through all available data, where every lead makes it easier to reach relevant documents or entities. Modern search is heavily powered by structured knowledge, but users still query using keywords or, at the very best, telegraphic 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 tackle entity-oriented search using graph-based approaches for representation and retrieval. In particular, we propose the graph-of-entity, a novel approach for indexing combined data, where terms, entities and their relations are jointly represented. We compare the graph-of-entity with the graph-of-word, a text-only model, verifying that, overall, it does not yet achieve a better performance, despite obtaining a higher precision. Our assessment was based on a small subset of the INEX 2009 Wikipedia Collection, created from a sample of 10 topics and respectively judged documents. The offline evaluation we do here is complementary to its counterpart from TREC 2017 OpenSearch track, where, during our participation, we had assessed graph-of-entity in an online setting, through team-draft interleaving. © José Devezas, Carla Lopes, and Sérgio Nunes.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14