Early Fusion Strategy for Entity-Relationship Retrieval
Abstract
We address the task of entity-relationship (E-R) retrieval, i.e, given a query characterizing types of two or more entities and relationships between them, retrieve the relevant tuples of related entities. Answering E-R queries requires gathering and joining evidence from multiple unstructured documents. In this work, we consider entity and relationships of any type, i.e, characterized by context terms instead of pre-defined types or relationships. We propose a novel IR-centric approach for E-R retrieval, that builds on the basic early fusion design pattern for object retrieval, to provide extensible entity-relationship representations, suitable for complex, multi-relationships queries. We performed experiments with Wikipedia articles as entity representations combined with relationships extracted from ClueWeb-09-B with FACC1 entity linking. We obtained promising results using 3 different query collections comprising 469 E-R queries.
Cite
@article{arxiv.1707.09075,
title = {Early Fusion Strategy for Entity-Relationship Retrieval},
author = {Pedro Saleiro and Natasa Milic-Frayling and Eduarda Mendes Rodrigues and Carlos Soares},
journal= {arXiv preprint arXiv:1707.09075},
year = {2017}
}
Comments
KG4IR (SIGIR workshop)