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» Learning probabilistic models of the Web
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SIGIR
2012
ACM
13 years 8 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...
CORR
2012
Springer
220views Education» more  CORR 2012»
14 years 2 months ago
Sparse Topical Coding
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
Jun Zhu, Eric P. Xing
HT
2006
ACM
16 years 11 days ago
Implementation and evaluation of a quality-based search engine
In this paper, an approach for the implementation of a qualitybased Web search engine is proposed. Quality retrieval is introduced and an overview on previous efforts to implement...
Thomas Mandl
BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
15 years 3 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
ADAPTIVE
2007
Springer
16 years 18 days ago
Semantic Web Technologies for the Adaptive Web
Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a...
Peter Dolog, Wolfgang Nejdl