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Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 1105-1108
Shengyue Ji , Department of Computer Science, UC Irvine, CA 92697-3435, USA
Chen Li , Department of Computer Science, UC Irvine, CA 92697-3435, USA
Guoliang Li , Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China
Jianhua Feng , Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China
ABSTRACT
TASTIER is a research project on the new information-access paradigm called type-ahead search, in which systems find answers to a keyword query on-the-fly as users type in the query. In this paper we study how to support fuzzy type-ahead search in TASTIER. Supporting fuzzy search is important when users have limited knowledge about the exact representation of the entities they are looking for, such as people records in an online directory. We have developed and deployed several such systems, some of which have been used by many people on a daily basis. The systems received overwhelmingly positive feedbacks from users due to their friendly interfaces with the fuzzy-search feature. We describe the design and implementation of the systems, and demonstrate several such systems. We show that our efficient techniques can indeed allow this search paradigm to scale on large amounts of data.
CITATION
Shengyue Ji, Chen Li, Guoliang Li, Jianhua Feng, "Efficient fuzzy type-ahead search in TASTIER", ICDE, 2010, 2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013 IEEE 29th International Conference on Data Engineering (ICDE) 2010, pp. 1105-1108, doi:10.1109/ICDE.2010.5447804
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