The Open UniversitySkip to content
 

Bias-variance analysis in estimating true query model for information retrieval

Zhang, Peng; Song, Dawei; Wang, Jun and Hou, Yue (2014). Bias-variance analysis in estimating true query model for information retrieval. Information Processing & Management, 50(1) pp. 199–217.

Full text available as:
[img]
Preview
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (398kB) | Preview
DOI (Digital Object Identifier) Link: https://doi.org/10.1016/j.ipm.2013.08.004
Google Scholar: Look up in Google Scholar

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.

Item Type: Journal Item
Copyright Holders: 2013 Elsevier Ltd.
ISSN: 0306-4573
Project Funding Details:
Funded Project NameProject IDFunding Body
Chinese National Program on Key Basic Research Project - 973 Program2013CB329304Not Set
Not Set61272265Natural Science Foundation of China
FP7 QONTEXT project247590EU
Chinese National Program on Key Basic Research Project - 973 Program2014CB744604Not Set
Not Set61070044Natural Science Foundation of China
Not Set61105702Natural Science Foundation of China
Keywords: information retrieval; query language model; bias-variance
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 38254
Depositing User: Dawei Song
Date Deposited: 03 Sep 2013 08:44
Last Modified: 09 Oct 2017 13:48
URI: http://oro.open.ac.uk/id/eprint/38254
Share this page:

Metrics

Altmetrics from Altmetric

Citations from Dimensions

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU