TY - GEN
T1 - Object-level vertical search
AU - Nie, Zaiqing
AU - Wen, Ji-Rong
AU - Ma, Wei-Ying
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2007
Y1 - 2007
N2 - Current web search engines essentially conduct document-level ranking and retrieval. However, structured information about realworld objects embedded in static webpages and online databases exists in huge amounts. We explore a new paradigm to enable web search at the object level in this paper, extracting and integrating web information for objects relevant to a specific application domain. We then rank these objects in terms of their relevance and popularity in answering user queries. In this paper, we introduce the overview and core technologies of object-level vertical search engines that have been implemented in two working systems: Libra Academic Search (http://libra.msra.cn) and Windows Live Product Search (http://products.live.com).
AB - Current web search engines essentially conduct document-level ranking and retrieval. However, structured information about realworld objects embedded in static webpages and online databases exists in huge amounts. We explore a new paradigm to enable web search at the object level in this paper, extracting and integrating web information for objects relevant to a specific application domain. We then rank these objects in terms of their relevance and popularity in answering user queries. In this paper, we introduce the overview and core technologies of object-level vertical search engines that have been implemented in two working systems: Libra Academic Search (http://libra.msra.cn) and Windows Live Product Search (http://products.live.com).
KW - Information integration
KW - Object-level ranking
KW - Web information extraction
KW - Web search
UR - http://www.scopus.com/inward/record.url?scp=38549134414&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-38549134414&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
T3 - CIDR 2007 - 3rd Biennial Conference on Innovative Data Systems Research
SP - 235
EP - 246
BT - CIDR 2007 - 3rd Biennial Conference on Innovative Data Systems Research
T2 - 3rd Biennial Conference on Innovative Data Systems Research, CIDR 2007
Y2 - 7 January 2007 through 10 January 2007
ER -