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Search, Information Retrieval, and Knowledge Management

Helping people to organize and find information


Knowledge workers need software that is easy to use and intuitive. They need to find their information long after they’ve forgotten where they put their documents and what they named their files. They also need better tools to help them find and consume information on the Internet. Information-retrieval and search technologies are critical to making this happen. We are pursuing research in information retrieval, filtering, and management, as well as the use of classification technologies and the development of systems and interfaces that will enrich the user experience.

 

Publications

Ali Mamdouh Elkahky, Yang Song, and Xiaodong He, A Multi-View Deep Learning Approach for User Modeling in Recommendation Systems, in WWW 2015, WWW – World Wide Web Consortium (W3C), May 2015.

Gennady Pekhimenko, Dimitrios Lymberopoulos, Oriana Riva, Karin Strauss, and Doug Burger, PocketTrend: Timely Identification and Delivery of Trending Search Content to Mobile Users, in Proceedings of the 24th International World Wide Web Conference (WWW '15), May 2015.

Wen Hua, Zhongyuan Wang, Haixun Wang, Kai Zheng, and Xiaofang Zhou, Short Text Understanding Through Lexical-Semantic Analysis, in International Conference on Data Engineering (ICDE), April 2015.

Emre Kıcıman, Towards Learning a Knowledge Base of Actions from Experiential Microblogs, in AAAI Spring Symposium on Knowledge Representation and Reasoning, AAAI - Association for the Advancement of Artificial Intelligence, 23 March 2015.

Lihong Li, Jin Young Kim, and Imed Zitouni, Toward Predicting the Outcome of an A/B Experiment for Search Relevance, in Proceedings of the 8th ACM International Conference on Web Search and Data Mining, ACM – Association for Computing Machinery, February 2015.

More publications ...