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Dynamic Information Retrieval Modeling
Wednesday, October 1, 2014, 11:00 am-12:00 pm Calendar
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Abstract

Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in big data sets (typically collected over long time spans) and models need to respond to these changes. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. This talk provides a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role.

Bio

Grace Hui Yang is an Assistant Professor in the Department of Computer Science at Georgetown University. Grace’s current research interests include session search, search engine evaluation, privacy-preserving information retrieval, and information organization. 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, and WWW since 2002. Grace co-chairs the SIGIR 2013 and SIGIR 2014 Doctoral Consortium, and serves as an area chair for SIGIR and program committee members in SIGIR, ACL, EMNLP, CIKM, WSDM, and KDD.

This talk is organized by Jimmy Lin