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
The Journal of Machine Learning Research
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The Turn: Integration of Information Seeking and Retrieval in Context (The Information Retrieval Series)
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Journal of the ACM (JACM)
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Exploratory search: from finding to understanding
Communications of the ACM - Supporting exploratory search
CHI '07 Extended Abstracts on Human Factors in Computing Systems
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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International Journal of Human-Computer Studies
Concept-based feature generation and selection for information retrieval
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IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A Semantic Imitation Model of Social Tag Choices
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DivRank: the interplay of prestige and diversity in information networks
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COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Concept-Based Information Retrieval Using Explicit Semantic Analysis
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FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
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Sometimes we search for simple facts. Other times we search for relationships between concepts. While existing information retrieval systems work well for simple searches, they are less satisfying for complex inquiries because of the ill-structured nature of many searches and the cognitive load involved in the search process. Search can be improved by leveraging the network of concepts that are maintained by collaborative knowledge bases such as Wikipedia. By treating exploratory search inquires as networks of concepts -- and then mapping documents to these concepts, exploratory search performance can be improved. This method is applied to an exploratory search task: given a journal abstract, abstracts are ranked based their relevancy to the seed abstract. The results show comparable relevancy scores to state of the art techniques while at the same time providing better diversity.