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KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 6 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
16 years 6 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
KDD
2003
ACM
214views Data Mining» more  KDD 2003»
16 years 6 months ago
Adaptive duplicate detection using learnable string similarity measures
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
Mikhail Bilenko, Raymond J. Mooney
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
16 years 6 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
16 years 6 months ago
Optimizing search engines using clickthrough data
This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system shoul...
Thorsten Joachims