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Zhang, Peng; Song, Dawei; Wang, Jun and Hou, Yue
(2014).
DOI: https://doi.org/10.1016/j.ipm.2013.08.004
Abstract
The estimation of query model is an important task in language modeling (LM) approaches to information retrieval (IR). The ideal estimation is expected to be not only effective in terms of high mean retrieval performance over all queries, but also stable in terms of low variance of retrieval performance across different queries. In practice, however, improving effectiveness can sacrifice stability, and vice versa. In this paper, we propose to study this tradeoff from a new perspective, i.e., the bias-variance tradeoff, which is a fundamental theory in statistics. We formulate the notion of bias-variance regarding retrieval performance and estimation quality of query models. We then investigate several estimated query models, by analyzing when and why the bias-variance tradeoff will occur, and how the bias and variance can be reduced simultaneously. A series of experiments on four TREC collections have been conducted to systematically evaluate our bias-variance analysis. Our approach and results will potentially form an analysis framework and a novel evaluation strategy for query language modeling.
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About
- Item ORO ID
- 38254
- Item Type
- Journal Item
- ISSN
- 0306-4573
- Project Funding Details
-
Funded Project Name Project ID Funding Body Chinese National Program on Key Basic Research Project - 973 Program 2013CB329304 Not Set Not Set 61272265 Natural Science Foundation of China FP7 QONTEXT project 247590 EU Chinese National Program on Key Basic Research Project - 973 Program 2014CB744604 Not Set Not Set 61070044 Natural Science Foundation of China Not Set 61105702 Natural Science Foundation of China - Keywords
- information retrieval; query language model; bias-variance
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2013 Elsevier Ltd.
- Depositing User
- Dawei Song