User interest modeling and its application for question recommendation in user-interactive question answering systems

► Question recommendation is used to facilitate users in UIQA systems to obtain interesting information. ► The topic-based user interest model is proposed for question recommendation. ► The topic model narrows down the semantic gap between questions in UIQA systems. In this paper, we propose a gener...

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Bibliographic Details
Published in:Information processing & management 2012-03, Vol.48 (2), p.218-233
Main Authors: Ni, Xingliang, Lu, Yao, Quan, Xiaojun, Wenyin, Liu, Hua, Bei
Format: Article
Language:English
Subjects:
Alliances
Automatic text analysis
Categories
Data acquisition
Data processing
Effectiveness studies
End users
Exact sciences and technology
Information and communication sciences
Information processing and retrieval
Information retrieval systems. Information and document management system
Information retrieval. Man machine relationship
Information science
Information science. Documentation
Management
Mathematical models
Mining
Online information retrieval
Performance evaluation
Question answering
Question answering systems
Research process. Evaluation
Sciences and techniques of general use
Topic model
User interest
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Summary:► Question recommendation is used to facilitate users in UIQA systems to obtain interesting information. ► The topic-based user interest model is proposed for question recommendation. ► The topic model narrows down the semantic gap between questions in UIQA systems. In this paper, we propose a generative model, the Topic-based User Interest (TUI) model, to capture the user interest in the User-Interactive Question Answering (UIQA) systems. Specifically, our method aims to model the user interest in the UIQA systems with latent topic method, and extract interests for users by mining the questions they asked, the categories they participated in and relevant answer providers. We apply the TUI model to the application of question recommendation, which automatically recommends to certain user appropriate questions he might be interested in. Data collection from Yahoo! Answers is used to evaluate the performance of the proposed model in question recommendation, and the experimental results show the effectiveness of our proposed model.
ISSN:0306-4573
1873-5371
DOI:10.1016/j.ipm.2011.09.002