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VLDB
2008
ACM
170views Database» more  VLDB 2008»
14 years 6 months ago
A multi-ranker model for adaptive XML searching
The evolution of computing technology suggests that it has become more feasible to offer access to Web information in a ubiquitous way, through various kinds of interaction device...
Ho Lam Lau, Wilfred Ng
IPM
2008
100views more  IPM 2008»
13 years 5 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
BMCBI
2008
118views more  BMCBI 2008»
13 years 5 months ago
Virtual screening of GPCRs: An in silico chemogenomics approach
The G-protein coupled receptor (GPCR) superfamily is currently the largest class of therapeutic targets. In silico prediction of interactions between GPCRs and small molecules is ...
Laurent Jacob, Brice Hoffmann, Véronique St...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 6 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
ERCIMDL
2006
Springer
204views Education» more  ERCIMDL 2006»
13 years 9 months ago
Comparing and Combining Two Approaches to Automated Subject Classification of Text
A machine-learning and a string-matching approach to automated subject classification of text were compared, as to their performance, advantages and downsides. The former approach ...
Koraljka Golub, Anders Ardö, Dunja Mladenic, ...