Identification of ambiguous queries in web search

• Published in: Information processing & management 2009-03, Vol.45 (2), p.216-229
• Main Authors: Song, Ruihua, Luo, Zhenxiao, Nie, Jian-Yun, Yu, Yong, Hon, Hsiao-Wuen
• Format: Article
• Language: English
• Subjects: Ambiguity; Ambiguous query; Broad topics; Classification; Exact sciences and technology; Information and communication sciences; Information processing and retrieval; Information retrieval. Man machine relationship; Information science. Documentation; Learning; Query classification; Query formulation; Query taxonomy; Research process. Evaluation; Sciences and techniques of general use; Search engines; Studies
• ISSN: 0306-4573; 1873-5371
• DOI: 10.1016/j.ipm.2008.09.005

It is widely believed that many queries submitted to search engines are inherently ambiguous (e.g., java and apple). However, few studies have tried to classify queries based on ambiguity and to answer “what the proportion of ambiguous queries is”. This paper deals with these issues. First, we clarify the definition of ambiguous queries by constructing the taxonomy of queries from being ambiguous to specific. Second, we ask human annotators to manually classify queries. From manually labeled results, we observe that query ambiguity is to some extent predictable. Third, we propose a supervised learning approach to automatically identify ambiguous queries. Experimental results show that we can correctly identify 87% of labeled queries with the approach. Finally, by using our approach, we estimate that about 16% of queries in a real search log are ambiguous.