Rank-preserving two-level caching for scalable search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Transparent Queries: investigation users' mental models of search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Effective site finding using link anchor information
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGIR Forum
Query type classification for web document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Engineering a multi-purpose test collection for web retrieval experiments
Information Processing and Management: an International Journal
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Integration of multiple evidences based on a query type for web search
Information Processing and Management: an International Journal
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Getting work done on the web: supporting transactional queries
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Coupling feature selection and machine learning methods for navigational query identification
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Web Search: Public Searching of the Web
Web Search: Public Searching of the Web
Transactional query identification in web search
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
The intention behind web queries
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Understanding and predicting personal navigation
Proceedings of the fourth ACM international conference on Web search and data mining
A multi-faceted approach to query intent classification
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Modeling transactional queries via templates
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Using site-level connections to estimate link confidence
Journal of the American Society for Information Science and Technology
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Queries submitted to search engines can be classified according to the user goals into three distinct categories: navigational, informational, and transactional. Such classification may be useful, for instance, as additional information for advertisement selection algorithms and for search engine ranking functions, among other possible applications. This paper presents a study about the impact of using several features extracted from the document collection and query logs on the task of automatically identifying the users' goals behind their queries. We propose the use of new features not previously reported in literature and study their impact on the quality of the query classification task. Further, we study the impact of each feature on different web collections, showing that the choice of the best set of features may change according to the target collection. The results obtained indicate the new proposed set of features improves the quality of the classification task when compared to previous proposals. We report experiments with two web collections where we were able to obtain 82.5% and 77.67% of overall accuracy when classifying queries according to the three distinct user goals studied.