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KDD
2002
ACM
293views Data Mining» more  KDD 2002»
16 years 7 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes
WSDM
2010
ACM
265views Data Mining» more  WSDM 2010»
16 years 4 months ago
Data-oriented Content Query System: Searching for Data into Text on the Web
As the Web provides rich data embedded in the immense contents inside pages, we witness many ad-hoc efforts for exploiting fine granularity information across Web text, such as We...
Kevin Chen-Chuan Chang, Mianwei Zhou, Tao Cheng
WSDM
2009
ACM
161views Data Mining» more  WSDM 2009»
16 years 1 months ago
Predicting the readability of short web summaries
Readability is a crucial presentation attribute that web summarization algorithms consider while generating a querybaised web summary. Readability quality also forms an important ...
Tapas Kanungo, David Orr
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
14 years 2 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
KDD
1997
ACM
169views Data Mining» more  KDD 1997»
15 years 11 months ago
Learning to Extract Text-Based Information from the World Wide Web
Thereis a wealthof informationto be minedfromnarrative text on the WorldWideWeb.Unfortunately, standard natural language processing (NLP)extraction techniques expect full, grammat...
Stephen Soderland