Modeling higher-order term dependencies in information retrieval using query hypergraphs

Many of the recent, and more effective, retrieval models have incorporated dependencies between the terms in the query. In this paper, we advance this query representation one step further, and propose a retrieval framework that models higher-order term dependencies, i.e., dependencies between arbitrary query concepts rather than just query terms. In order to model higher-order term dependencies, we represent a query using a hypergraph structure – a generalization of a graph, where a (hyper)edge connects an arbitrary subset of vertices. A vertex in a query hypergraph corresponds to an individual query concept, and a dependency between a subset of these vertices is modeled through a hyperedge. An extensive empirical evaluation using both newswire and web corpora demonstrates that query representation using hypergraphs is highly beneficial for verbose natural language queries. For these queries, query hypergraphs significantly improve the retrieval effectiveness of several state-o...

• Type: Journal
• Year: 2012
• Where: SIGIR
• Authors: Michael Bendersky, W. Bruce Croft
• Keywords: Arbitrary Subset, Information Storage And Retrieval, Information Technology, Natural Language Queries, SIGIR 2012