Automatic term mismatch diagnosis for selective query expansion

People are seldom aware that their search queries frequently mismatch a majority of the relevant documents. This may not be a big problem for topics with a large and diverse set of relevant documents, but would largely increase the chance of search failure for less popular search needs. We aim to address the mismatch problem by developing accurate and simple queries that require minimal effort to construct. This is achieved by targeting retrieval interventions at the query terms that are likely to mismatch relevant documents. For a given topic, the proportion of relevant documents that do not contain a term measures the probability for the term to mismatch relevant documents, or the term mismatch probability. Recent research demonstrates that this probability can be estimated reliably prior to retrieval. Typically, it is used in probabilistic retrieval models to provide query dependent term weights. This paper develops a new use: Automatic diagnosis of term mismatch. A search engine c...

• Type: Journal
• Year: 2012
• Where: SIGIR
• Authors: Le Zhao, Jamie Callan
• Keywords: Automatic Query Expansion, Information Technology, Query Reformulation, SIGIR 2012, Term Weights