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KDD
2009
ACM
245views Data Mining» more  KDD 2009»
16 years 7 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
KDD
2009
ACM
243views Data Mining» more  KDD 2009»
16 years 7 months ago
Exploiting Wikipedia as external knowledge for document clustering
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
KDD
2009
ACM
262views Data Mining» more  KDD 2009»
16 years 7 months ago
Sentiment analysis of blogs by combining lexical knowledge with text classification
The explosion of user-generated content on the Web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the disc...
Prem Melville, Wojciech Gryc, Richard D. Lawrence
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
16 years 7 months ago
Seven pitfalls to avoid when running controlled experiments on the web
Controlled experiments, also called randomized experiments and A/B tests, have had a profound influence on multiple fields, including medicine, agriculture, manufacturing, and adv...
Thomas Crook, Brian Frasca, Ron Kohavi, Roger Long...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 7 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
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