Conference Proceedings


Gareth J.F. Jones
Jennifer Foster
Piyush Arora


Computer Science

pseudo relevance feedback approaches word embeddings experimental query expansion improvement retrieval models sentence retrieval

Query expansion for sentence retrieval using pseudo relevance feedback and word embedding (2017)

Abstract This study investigates the use of query expansion (QE) methods in sentence retrieval for non-factoid queries to address the query-document term mismatch problem. Two alternative QE approaches: i) pseudo relevance feedback (PRF), using Robertson term selection, and ii) word embeddings (WE) of query words, are explored. Experiments are carried out on the WebAP data set developed using the TREC GOV2 collection. Experimental results using P@10, NDCG@10 and MRR show that QE using PRF achieves a statistically significant improvement over baseline retrieval models, but that while WE also improves over the baseline, this is not statistically significant. A method combining PRF and WE expansion performs consistently better than using only the PRF method.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Status = Published

Full list of authors on original publication

Gareth J.F. Jones, Jennifer Foster, Piyush Arora

Experts in our system

Gareth J. F. Jones
Dublin City University
Total Publications: 297
Jennifer Foster
Dublin City University
Total Publications: 51
Piyush Arora
Dublin City University
Total Publications: 15