Type

Conference Proceedings

Authors

Gareth J. F. Jones
Johannes Leveling
Debasis Ganguly

Subjects

Computer Science

Topics
information retrieval mean average precision rlm modeling language sbqe relevance model sentence based query expansion map

Query expansion for language modeling using sentence similarities (2011)

Abstract We propose a novel method of query expansion for Language Modeling (LM) in Information Retrieval (IR) based on the similarity of the query with sentences in the top ranked documents from an initial retrieval run. In justification of our approach, we argue that the terms in the expanded query obtained by the proposed method roughly follow a Dirichlet distribution which, being the conjugate prior of the multinomial distribution used in the LM retrieval model, helps the feedback step. IR experiments on the TREC ad-hoc retrieval test collections using the sentence based query expansion (SBQE) show a significant increase in Mean Average Precision (MAP) compared to baselines obtained using standard term-based query expansion using LM selection score and the Relevance Model (RLM). The proposed approach to query expansion for LM increases the likelihood of generation of the pseudo-relevant documents by adding sentences with maximum term overlap with the query sentences for each top ranked pseudorelevant document thus making the query look more like these documents. A per topic analysis shows that the new method hurts less queries compared to the baseline feedback methods, and improves average precision (AP) over a broad range of queries ranging from easy to difficult in terms of the initial retrieval AP. We also show that the new method is able to add a higher number of good feedback terms (the golden standard of good terms being the set of terms added by True Relevance Feedback). Additional experiments on the challenging search topics of the TREC-2004 Robust track show that the new method is able to improve MAP by 5.7% without the use of external resources and query hardness prediction typically used for these topics.
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 -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Next Generation Localisation (CNGL)
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Information retrieval
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Gareth J. F. Jones, Johannes Leveling, Debasis Ganguly

Experts in our system

1
Gareth J. F. Jones
Dublin City University
Total Publications: 297
 
2
Johannes Leveling
Dublin City University
Total Publications: 66
 
3
Debasis Ganguly
Dublin City University
Total Publications: 40