Top-k retrieval using facility location analysis

Zuccon, Guido, Azzopardi, Leif, Zhang, Dell, & Wang, Jun (2012) Top-k retrieval using facility location analysis. Lecture Notes in Computer Science : Advances in Information Retrieval, 7224, pp. 305-316.

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The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.

Impact and interest:

18 citations in Scopus
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ID Code: 72188
Item Type: Journal Article
Refereed: Yes
Keywords: Top-k retrieval, Facility location analysis, information storage and retrieval
DOI: 10.1007/978-3-642-28997-2_26
ISBN: 978-3-642-28997-2
ISSN: 1611-3349
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Springer
Copyright Statement: The original publication is available at SpringerLink
Deposited On: 28 May 2014 23:43
Last Modified: 30 Jun 2017 18:23

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