Optimizing search by showing results in context
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using terminological feedback for web search refinement: a log-based study
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Examining the effectiveness of real-time query expansion
Information Processing and Management: an International Journal
Acquiring ontological knowledge from query logs
Proceedings of the 16th international conference on World Wide Web
Query suggestions for mobile search: understanding usage patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Context-aware query suggestion by mining click-through and session data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Query suggestion using hitting time
Proceedings of the 17th ACM conference on Information and knowledge management
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Learning latent semantic relations from clickthrough data for query suggestion
Proceedings of the 17th ACM conference on Information and knowledge management
Organizing Suggestions in Autocompletion Interfaces
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Web Query Recommendation via Sequential Query Prediction
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Named entity recognition in query
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A comparison of query and term suggestion features for interactive searching
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
From "Dango" to "Japanese Cakes": Query Reformulation Models and Patterns
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
An optimization framework for query recommendation
Proceedings of the third ACM international conference on Web search and data mining
Effects of popularity and quality on the usage of query suggestions during information search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Clustering query refinements by user intent
Proceedings of the 19th international conference on World wide web
Optimal rare query suggestion with implicit user feedback
Proceedings of the 19th international conference on World wide web
Building taxonomy of web search intents for name entity queries
Proceedings of the 19th international conference on World wide web
A structured approach to query recommendation with social annotation data
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Post-ranking query suggestion by diversifying search results
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
The wisdom of advertisers: mining subgoals via query clustering
Proceedings of the 21st ACM international conference on Information and knowledge management
Time-aware structured query suggestion
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
When do people use query suggestion? A query suggestion log analysis
Information Retrieval
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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.