Word or Phrase? Learning Which Unit to Stress for Information Retrieval

Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, pages 1048–1056, Suntec, Singapore, 2-7 August 2009. c⃝2009 ACL and AFNLP Word or Phrase? Learning Which Unit to Stress for Information Retrieval∗ Young-In Song† and Jung-Tae Lee‡ and Hae-Chang Rim‡ †Microsoft Research Asia, Beijing, China ‡Dept. of Computer & Radio Communications Engineering, Korea University, Seoul, Korea yosong@microsoft.com†, {jtlee,rim}@nlp.korea.ac.kr‡ Abstract The use of phrases in retrieval models has been proven to be helpful in the literature, but no particular research addresses the problem of discriminating phrases that are likely to degrade the retrieval performance from the ones that do not. In this paper, we present a retrieval framework that utilizes both words and phrases flexibly, followed by a general learning-to-rank method for learning the potential contribution of a phrase in retrieval. We also present use- ful features that reflect the compositional- ity and discriminative power of a phrase and its constituent words for optimizing the weights of phrase use in phrase-based retrieval models. Experimental results on the TREC collections show that our pro- posed method is effective. 1 Introduction Various researches have improved the quality of information retrieval by relaxing the tradi- tional ‘bag-of-words’ assumption with the use of phrases. (Miller et al., 1999; Song and Croft, 1999) explore the use n-grams in retrieval mod- els. (Fagan, 1987; Gao et al., 2004; Met- zler and Croft, 2005; Tao and Zhai, 2007) use statistically-captured term dependencies within a query. (Strzalkowski et al., 1994; Kraaij and Pohlmann, 1998; Arampatzis et al., 2000) study the utility of various kinds of syntactic phrases. Although use of phrases clearly helps, there still exists a fundamental but unsolved question: Do all phrases contribute an equal amount of increase in the performance of information retrieval models? Let us consider a search query ‘World Bank Crit- icism’, which has the following phrases: ‘world ∗This work was done while Young-In Song was with the Dept. of Computer & Radio Communications Engineering, Korea University. bank’ and ‘bank criticism’. Intuitively, the for- mer should be given more importance than its con- stituents ‘world’ and ‘bank’, since the meaning of the original phrase cannot be predicted from the meaning of either constituent. In contrast, a relatively less attention could be paid to the lat- ter ‘bank criticism’, because there may be alter- nate expressions, of which the meaning is still pre- served, that could possibly occur in relevant docu- ments. However, virtually all the researches ig- nore the relation between a phrase and its con- stituent words when combining both words and phrases in a retrieval model. Our approach to phrase-based retrieval is moti- vated from the following linguistic intuitions: a) phrases have relatively different degrees of signif- icance, and b) the influence of a phrase should be differentiated based on the phrase’s constituents in retrieval models. In this paper, we start out by presenting a simple language modeling-based re- trieval model that utilizes both words and phrases in ranking with use of parameters that differenti- ate …

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