Automatically identifying localizable queries

Personalization of web search results as a technique for improving user satisfaction has received notable attention in the research community over the past decade. Much of this work focuses on modeling and establishing a profile for each user to aid in personalization. Our work takes a more querycentric approach. In this paper, we present a method for efficient, automatic identification of a class of queries we define as localizable from a web search engine query log. We determine a set of relevant features and use conventional machine learning techniques to classify queries. Our experiments find that our technique is able to identify localizable queries with 94% accuracy. Categories and Subject Descriptors H.3.3 [Information Storage And Retrieval]: Information Search and Retrieval--Search process; I.5.4 [Pattern Recognition]: Applications--Text processing General Terms Experimentation, Human Factors, Measurement Keywords Localizable query, web search, machine learning

• Type: Journal
• Year: 2008
• Where: SIGIR
• Authors: Michael J. Welch, Junghoo Cho
• Keywords: Information Technology, Localizable Queries, SIGIR 2008, Web Search, Web Search Engine