Multitasking information seeking and searching processes
Journal of the American Society for Information Science and Technology
A practical web-based approach to generating topic hierarchy for text segments
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Implicit user modeling for personalized search
Proceedings of the 14th ACM international conference on Information and knowledge management
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Defining a session on Web search engines: Research Articles
Journal of the American Society for Information Science and Technology
Query Modifications Patterns During Web Searching
ITNG '07 Proceedings of the International Conference on Information Technology
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
Proceedings of the 17th ACM conference on Information and knowledge management
A survey on session detection methods in query logs and a proposal for future evaluation
Information Sciences: an International Journal
The ESA retrieval model revisited
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Models of searching and browsing: languages, studies, and applications
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Analyzing and evaluating query reformulation strategies in web search logs
Proceedings of the 18th ACM conference on Information and knowledge management
Multitasking during Web search sessions
Information Processing and Management: an International Journal - Special issue: Formal methods for information retrieval
Similarity measures for short segments of text
ECIR'07 Proceedings of the 29th European conference on IR research
Identifying task-based sessions in search engine query logs
Proceedings of the fourth ACM international conference on Web search and data mining
The semantics of query modification
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Semantic search log analysis: A method and a study on professional image search
Journal of the American Society for Information Science and Technology
Modeling and analysis of cross-session search tasks
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Query session detection as a cascade
Proceedings of the 20th ACM international conference on Information and knowledge management
Towards optimum query segmentation: in doubt without
Proceedings of the 21st ACM international conference on Information and knowledge management
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Search mission detection aims at identifying those queries a user submits for the same information need. Such knowledge offers interesting insights into behavioral usage patterns and often can help to better support a user. However, most existing query log studies focus on search sessions only (consecutive queries for the same need) and ignore multitasking behavior (interleaved information needs) as well as hierarchies of short-term search goals in multiple sessions that form a long-term search task such as vacation planning. To better understand the dialog between user and search engine we distinguish between (1) physical search sessions, characterized by the time gap between queries, (2) logical search sessions, characterized by consecutive queries for the same information need within a physical session, and (3) search missions, characterized by logical sessions, multitasking behavior, and hierarchical goals. Our contributions are threefold. First, we present a new algorithm for logical session detection, which follows the state-of-the-art cascading method's rationale of combining effectiveness with efficiency. Our approach is applicable within the time-critical online scenario, where a search engine tries to support users by incorporating knowledge about their search history on the fly, as well as within the offline scenario, where the objective is to accurately partition a collected log. We improve several steps of the cascading method, among others by exploiting Linked Open Data information. Second, we demonstrate our new algorithm's applicability to accurately detect search missions. Third, we introduce a new publicly available corpus of 8800 queries labeled with session and mission information.