ECIR2012 Best Paper: Top-k Retrieval using Facility Location Analysis
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.
[bibtex file=mypublications.bib key=ecir2012]