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Incorporating intra-query term dependencies in an Aspect Query Language Model

Song, Dawei; Shi, Yanjie; Zhang, Peng; Huang, Qiang; Kruschwitz, Udo; Hou, Yuexian and Wang, Bo (2015). Incorporating intra-query term dependencies in an Aspect Query Language Model. Computational Intelligence, 31(4) pp. 699–720.

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Query language modeling based on relevance feedback has been widely applied to improve the effectiveness of information retrieval. However, intra-query term dependencies (i.e., the dependencies between different query terms and term combinations) have not yet been sufficiently addressed in the existing approaches. This paper aims to investigate this issue within a comprehensive framework, namely the Aspect Query Language Model (AM). We propose to extend the AM with a Hidden Markov Model (HMM) structure, to incorporate the intra-query term dependencies and learn the structure of a novel Aspect Hidden Markov Model (AHMM) for query language modeling. In the proposed AHMM, the combinations of query terms are viewed as latent variables representing query aspects. They further form an Ergodic HMM, where the dependencies between latent variables (nodes) are modelled as the transitional probabilities. The segmented chunks from the feedback documents are considered as observables of the HMM. Then the AHMM structure is optimized by the HMM, which can estimate the prior of the latent variables and the probability distribution of the observed chunks. Our extensive experiments on three large scale TREC collections have shown that our method not only significantly outperforms a number of strong baselines in terms of both effectiveness and robustness, but also achieves better results than the AM and another state-of-the-art approach, namely the Latent Concept Expansion (LCE) model.

Item Type: Journal Item
Copyright Holders: 2014 Wiley Periodicals, Inc.
ISSN: 1467-8640
Project Funding Details:
Funded Project NameProject IDFunding Body
973 Program2013CB329304Chinese National Program on Key Basic
Not Set61272265Natural Science Foundation of China
Not Set61070044Natural Science Foundation of China
Not Set61105702Natural Science Foundation of China
Framework 7 Marie-Curie International Research Staff Exchange Programme247590EU
Keywords: information retrieval; Query Language Model; Aspect Hidden Markov Model; intra-query term dependency; query decomposition
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 40781
Depositing User: Dawei Song
Date Deposited: 04 Sep 2014 09:11
Last Modified: 07 Dec 2018 22:57
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