Research Repository

Incorporating Intra-Query Term Dependencies in an Aspect Query Language Model

Song, D and Shi, Y and Zhang, P and Huang, Q and Kruschwitz, U and Hou, Y and Wang, B (2015) 'Incorporating Intra-Query Term Dependencies in an Aspect Query Language Model.' Computational Intelligence, 31 (4). 699 - 720. ISSN 0824-7935

Full text not available from this repository.

Abstract

© 2014 Wiley Periodicals, Inc. ©2014 Wiley Periodicals, Inc. 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 article 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 HMM (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 modeled 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 text retrieval conference (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 model.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 19 May 2015 11:15
Last Modified: 23 Jan 2019 01:15
URI: http://repository.essex.ac.uk/id/eprint/13724

Actions (login required)

View Item View Item