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» Improving Web Search Relevance with Semantic Features
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WWW
2008
ACM
16 years 2 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
WSDM
2010
ACM
215views Data Mining» more  WSDM 2010»
15 years 11 months ago
GeoFolk: Latent spatial semantics in Web 2.0 social media
We describe an approach for multi-modal characterization of social media by combining text features (e.g. tags as a prominent example of short, unstructured text labels) with spat...
Sergej Sizov
CIKM
2009
Springer
15 years 8 months ago
Annotating wikipedia articles with semantic tags for structured retrieval
Structured retrieval aims at exploiting the structural information of documents when searching for documents. Structured retrieval makes use of both content and structure of docum...
Saravadee Sae Tan, Tang Enya Kong, Gian Chand Sodh...
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 1 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
117
Voted
SEMWEB
2010
Springer
14 years 11 months ago
Preference-Based Web Service Composition: A Middle Ground between Execution and Search
Abstract. Much of the research on automated Web Service Composition (WSC) relates it to an AI planning task, where the composition is primarily done offline prior to execution. Rec...
Shirin Sohrabi, Sheila A. McIlraith