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» Search Engines that Learn from Implicit Feedback
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KER
2007
90views more  KER 2007»
14 years 11 months ago
PLTOOL: A knowledge engineering tool for planning and learning
AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will tra...
Susana Fernández, Daniel Borrajo, Raquel Fu...
108
Voted
TCBB
2011
14 years 6 months ago
Learning Genetic Regulatory Network Connectivity from Time Series Data
Recent experimental advances facilitate the collection of time series data that indicate which genes in a cell are expressed. This paper proposes an efficient method to generate th...
Nathan A. Barker, Chris J. Myers, Hiroyuki Kuwahar...
CIVR
2010
Springer
204views Image Analysis» more  CIVR 2010»
15 years 2 months ago
Utilizing related samples to learn complex queries in interactive concept-based video search
One of the main challenges in interactive concept-based video search is the insufficient relevant sample problem, especially for queries with complex semantics. To address this pr...
Jin Yuan, Zheng-Jun Zha, Zhengdong Zhao, Xiangdong...
WWW
2010
ACM
15 years 5 months ago
Actively predicting diverse search intent from user browsing behaviors
This paper is concerned with actively predicting search intent from user browsing behavior data. In recent years, great attention has been paid to predicting user search intent. H...
Zhicong Cheng, Bin Gao, Tie-Yan Liu
WSDM
2012
ACM
258views Data Mining» more  WSDM 2012»
13 years 6 months ago
Large-scale analysis of individual and task differences in search result page examination strategies
Understanding the impact of individual and task differences on search result page examination strategies is important in developing improved search engines. Characterizing these e...
Georg Buscher, Ryen W. White, Susan T. Dumais, Jef...