JOURNAL ARTICLE

Entity-Based Relevance Feedback for Document Retrieval

Abstract

There is a long history of work on using relevance feedback for ad hoc document retrieval. The main types of relevance feedback studied thus far are for documents, passages and terms. We explore the merits of using relevance feedback provided for entities in an entity repository. We devise retrieval methods that can utilize relevance feedback provided for tokens whether entities or terms. Empirical evaluation shows that using entity relevance feedback falls short with respect to utilizing term feedback on average, but is much more effective for difficult queries. Furthermore, integrating term and entity relevance feedback is of clear merit; e.g., for augmenting minimal document feedback. We also contrast approaches to presenting entities and terms for soliciting relevance feedback.

Keywords:
Relevance feedback Relevance (law) Computer science Information retrieval Term (time) Artificial intelligence Image retrieval

Metrics

1
Cited By
0.62
FWCI (Field Weighted Citation Impact)
54
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Information Retrieval and Search Behavior
Physical Sciences →  Computer Science →  Information Systems
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

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