Sciweavers

120 search results - page 1 / 24
» Learning to rank with multi-aspect relevance for vertical se...
Sort
View
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
CIKM
2011
Springer
12 years 7 months ago
Learning to aggregate vertical results into web search results
Aggregated search is the task of integrating results from potentially multiple specialized search services, or verticals, into the Web search results. The task requires predicting...
Jaime Arguello, Fernando Diaz, Jamie Callan
CIDR
2007
155views Algorithms» more  CIDR 2007»
13 years 9 months ago
Object-level Vertical Search
Current web search engines essentially conduct document-level ranking and retrieval. However, structured information about realworld objects embedded in static webpages and online...
Zaiqing Nie, Ji-Rong Wen, Wei-Ying Ma
SIGIR
2012
ACM
11 years 10 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...
ECTEL
2007
Springer
14 years 1 months ago
Relevance Ranking Metrics for Learning Objects
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...
Xavier Ochoa, Erik Duval