This event took place on 4th March 2008 at 11:30am (11:30 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA
Web is evolving from time to time, more and more intelligent search engines are also emerging over time. the Traditional Web is composed of many unstructured Web pages. These pages are linked together and mainly for human reading. We focus on how to crawl more pages, improve search relevance or make search interactions simpler. Accordingly, we build the general search engines, the vertical search engines and the meta search engines. The emergence of Web 2.0 lowers the barrier for contribution. More people are involved and make the Web social. We focus on how to elaborate user involved data. Accordingly, we develop blog search, wiki search and tag enhanced search. The Semantic Web is composed of structured interlinked data. These data includes schema, axiom definitions and related assertions. It is mainly for machine understanding. We focus on how to learn or populate ontologies from the traditional Web, do search on the combination of Web ontology and Web pages, integrate reasoning with search to the Web scale or do semantic search using keyword queries.
Web is evolving from time to time, more and more intelligent search engines are also emerging over time. the Traditional Web is composed of many unstructured Web pages. These pages are linked together and mainly for human reading. We focus on how to crawl more pages, improve search relevance or make search interactions simpler. Accordingly, we build the general search engines, the vertical search engines and the meta search engines. The emergence of Web 2.0 lowers the barrier for contribution. More people are involved and make the Web social. We focus on how to elaborate user involved data. Accordingly, we develop blog search, wiki search and tag enhanced search. The Semantic Web is composed of structured interlinked data. These data includes schema, axiom definitions and related assertions. It is mainly for machine understanding. We focus on how to learn or populate ontologies from the traditional Web, do search on the combination of Web ontology and Web pages, integrate reasoning with search to the Web scale or do semantic search using keyword queries.
Click below to play the event (51 minutes)