Abstract:
Current Web search engine can be considered a page-level general search engine whose main functionality is to rank web pages according to their relevance to a given query. However, there are various kinds of objects embedded in static Web pages or Web databases. Typical objects are people, products, papers, organizations, etc. We can imagine that if these objects can be extracted and integrated from the Web, powerful object-level search engines can be built to meet users' information needs more precisely. In this talk, I will discuss this new trend on building what we call "object-level search engines". The research problems that we need to address include large scale web classification, object-level information extraction, object identification and integration, and object relationship mining and ranking. I introduce the overview and core technologies of object-level search engines that have been implemented in three working systems: Libra Academic Search (http://libra.msra.cn), Windows Live Product Search (http://products.live.com), and Guanxi – a search engine for entity relationship discovery (http://renlifang.msra.cn).
Bio:
Zaiqing Nie is a lead researcher in the Web Search & Mining Group at Microsoft Research Asia. He graduated in May 2004 with a Ph.D. in Computer Science from Arizona State University. He received both his Master and Bachelor of Engineering degree in Computer Science from Tsinghua University. His research interests include data mining, machine learning, Web information integration and retrieval. Nie has many publications in prestigious conferences and journals including SIGKDD, ICML, WWW, CIDR, ICDE, TKDE, and JMLR. His recent academic activities include program committee co-chair of IIWeb 2007 and program committee member of KDD 2008, SIGIR 2008, WWW 2008, ICML 2008, ACL 2008, AAAI 2008 etc. Some technologies he developed have been transferred to Microsoft products/services including Windows Live Product Search and Windows Live Search in China, Libra Academic Search, and Renlifang Guanxi Search.
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