Dynamic Information Retrieval Modeling

Author:   Grace Hui Yang ,  Marc Sloan ,  Jun Wang
Publisher:   Springer International Publishing AG
ISBN:  

9783031011733


Pages:   126
Publication Date:   16 June 2016
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Dynamic Information Retrieval Modeling


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Author:   Grace Hui Yang ,  Marc Sloan ,  Jun Wang
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Weight:   0.293kg
ISBN:  

9783031011733


ISBN 10:   3031011732
Pages:   126
Publication Date:   16 June 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.
Language:   English

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Grace Hui Yang is an Assistant Professor in the Department of Computer Science at Georgetown University. Grace's research interests include information retrieval, machine learning, natural language processing and text mining, with the current focus on dynamic search, search engine evaluation, and privacy-preserving information retrieval. Prior to this, she conducted research on question answering, ontology construction, near-duplicate detection, multimedia information retrieval, and opinion and sentiment detection. The results of her research have been published in SIGIR, CIKM, ACL, TREC, ECIR, ICTIR, and WWW since 2002. She was a recipient of the National Science Foundation Faculty Early Career Development (CAREER) Award. Grace co-organized the TREC Dynamic Domain Track and served as area chairs in SIGIR and ACL. She also served in the Information Retrieval Journal Editorial Board.Marc Sloan has completed a Ph.D. in Information Retrieval at University College London; his thesis was titled Probabilistic Modeling in Dynamic Information Retrieval. His research interests include applying reinforcement learning techniques such as multi-armed bandits and POMDPs to IR learning systems over time, contextual session search and query suggestion. Marc has published and presented IR research in top-tier conferences and journals such as WWW, SIGIR, WSDM, ICTIR and the Information Retrieval Journal. He has interned at Microsoft Research working on contextual, session based search result blending.Jun Wang is a Reader in Computer Science, University College London, and the Founding Director of MSc Web Science and Big Data Analytics. His main research interests are in the areas of information retrieval, data mining and online advertising. He was a recipient of the Beyond Search award sponsored by Microsoft Research, US, in 2007; he also received the Best Doctoral Consortium award in ACM SIGIR06 for his work on collaborative filtering, the Best Paper Prizes in ECIR09 andECIR12 for information retrieval, and the Best Paper Prize in ADKDD14 for computational advertising. He is also one of the recipients of Yahoo! FREP award 2014. He is an Area Chair of ACM SIGIR05 and has been a Senior PC member of ACM CIKM since 2012

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