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» Top-k learning to rank: labeling, ranking and evaluation
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IS
2007
14 years 9 months ago
A co-training framework for searching XML documents
In this paper, we study the use of XML tagged keywords (or simply key-tags) to search an XML fragment in a collection of XML documents. We present techniques that are able to empl...
Wilfred Ng, Ho Lam Lau
FCSC
2007
159views more  FCSC 2007»
14 years 9 months ago
Ranking with uncertain labels and its applications
1 The techniques for image analysis and classi cation generally consider the image sample labels xed and without uncertainties. The rank regression problem is studied in this pape...
Shuicheng Yan, Huan Wang, Jianzhuang Liu, Xiaoou T...
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
15 years 4 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
VLDB
1999
ACM
127views Database» more  VLDB 1999»
15 years 1 months ago
Evaluating Top-k Selection Queries
In many applications, users specify target values for certain attributes, without requiring exact matches to these values in return. Instead, the result to such queries is typical...
Surajit Chaudhuri, Luis Gravano
SIGMOD
2008
ACM
206views Database» more  SIGMOD 2008»
15 years 9 months ago
Ad-hoc aggregations of ranked lists in the presence of hierarchies
A variety of web sites and web based services produce textual lists at varying time granularities ranked according to several criteria. For example, Google Trends produces lists o...
Nilesh Bansal, Sudipto Guha, Nick Koudas