The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Making large-scale support vector machine learning practical
Advances in kernel methods
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Time-dependent semantic similarity measure of queries using historical click-through data
Proceedings of the 15th international conference on World Wide Web
Less is more: probabilistic models for retrieving fewer relevant documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search
ACM Transactions on Information Systems (TOIS)
Investigating behavioral variability in web search
Proceedings of the 16th international conference on World Wide Web
Editorial: Evaluating exploratory search systems
Information Processing and Management: an International Journal
SearchBar: a search-centric web history for task resumption and information re-finding
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predicting diverse subsets using structural SVMs
Proceedings of the 25th international conference on Machine learning
Novelty and diversity in information retrieval evaluation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs
Proceedings of the 17th ACM conference on Information and knowledge management
Smoothing clickthrough data for web search ranking
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Redundancy, diversity and interdependent document relevance
ACM SIGIR Forum
Classification-enhanced ranking
Proceedings of the 19th international conference on World wide web
Discounted cumulated gain based evaluation of multiple-query IR sessions
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Search behaviors in different task types
Proceedings of the 10th annual joint conference on Digital libraries
Personalizing information retrieval for multi-session tasks: the roles of task stage and task type
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Interactive retrieval based on faceted feedback
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Studying trailfinding algorithms for enhanced web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Learning to rank query reformulations
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Predicting short-term interests using activity-based search context
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Proceedings of the fourth ACM international conference on Web search and data mining
Modeling and analysis of cross-session search tasks
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Evaluating multi-query sessions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Proceedings of the 20th ACM international conference on Information and knowledge management
Structured learning of two-level dynamic rankings
Proceedings of the 20th ACM international conference on Information and knowledge management
Efficient query rewrite for structured web queries
Proceedings of the 20th ACM international conference on Information and knowledge management
Building the trail best traveled: effects of domain knowledge on web search trailblazing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Search, interrupted: understanding and predicting search task continuation
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Anticipatory search: using context to initiate search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Task tours: helping users tackle complex search tasks
Proceedings of the 21st ACM international conference on Information and knowledge management
Struggling or exploring?: disambiguating long search sessions
Proceedings of the 7th ACM international conference on Web search and data mining
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Current research on web search has focused on optimizing and evaluating single queries. However, a significant fraction of user queries are part of more complex tasks [20] which span multiple queries across one or more search sessions [26,24]. An ideal search engine would not only retrieve relevant results for a user's particular query but also be able to identify when the user is engaged in a more complex task and aid the user in completing that task [29,1]. Toward optimizing whole-session or task relevance, we characterize and address the problem of intrinsic diversity (ID) in retrieval [30], a type of complex task that requires multiple interactions with current search engines. Unlike existing work on extrinsic diversity [30] that deals with ambiguity in intent across multiple users, ID queries often have little ambiguity in intent but seek content covering a variety of aspects on a shared theme. In such scenarios, the underlying needs are typically exploratory, comparative, or breadth-oriented in nature. We identify and address three key problems for ID retrieval: identifying authentic examples of ID tasks from post-hoc analysis of behavioral signals in search logs; learning to identify initiator queries that mark the start of an ID search task; and given an initiator query, predicting which content to prefetch and rank.