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» Information Retrieval in Folksonomies: Search and Ranking
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SIGIR
2010
ACM
13 years 11 months ago
Inferring user intent in web search by exploiting social annotations
In this paper, we present a folksonomy-based approach for implicit user intent extraction during a Web search process. We present a number of result re-ranking techniques based on...
Jose M. Conde, David Vallet, Pablo Castells
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difļ¬cul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
CIKM
2008
Springer
13 years 9 months ago
Using tag semantic network for keyphrase extraction in blogs
Folksonomies provide a comfortable way to search and browse the blogosphere. As the tags in the blogosphere are sparse, ambiguous and too general, this paper proposes both a super...
Lizhen Qu, Christof Müller, Iryna Gurevych
CIKM
2005
Springer
14 years 1 months ago
Supporting ranked search in parallel search cluster networks
We investigate how to support ranked keyword search in a Parallel Search Cluster Network, which is a newly proposed peer-to-peer network overlay. In particular, we study how to eļ...
Fang Xiong, Qiong Luo, Dyce Jing Zhao
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 speciļ¬c domains. The meaning of relevance in these verticals is domain-speciļ¬c and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...