document: Structured query suggestion for specialization and parallel movement : effect on search behaviors Query suggestion , which enables the user to revise a query with a single click , has become one of the most fundamental features of Web search engines . However , it is often difficult for the user to choose from a list of query suggestions , and to understand the relation between an input query and suggested ones . In this paper , we propose a new method to present query suggestions to the user , which has been designed to help two popular query reformulation actions , namely , specialization ( e.g. from `` nikon '' to `` nikon camera '' ) and parallel movement ( e.g. from `` nikon camera '' to `` canon camera '' ) . Using a query log collected from a popular commercial Web search engine , our prototype called SParQS classifies query suggestions into automatically generated categories and generates a label for each category . Moreover , SParQS presents some new entities as alternatives to the original query ( e.g. `` canon '' in response to the query `` nikon '' ) , together with their query suggestions classified in the same way as the original query 's suggestions . We conducted a task-based user study to compare SParQS with a traditional `` flat list '' query suggestion interface . Our results show that the SParQS interface enables subjects to search more successfully than the flat list case , even though query suggestions presented were exactly the same in the two interfaces . In addition , the subjects found the query suggestions more helpful when they were presented in the SParQS interface rather than in a flat list .
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