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KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 7 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 7 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
KDD
2005
ACM
140views Data Mining» more  KDD 2005»
16 years 7 months ago
Graphs over time: densification laws, shrinking diameters and possible explanations
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
Jure Leskovec, Jon M. Kleinberg, Christos Faloutso...
KDD
2005
ACM
125views Data Mining» more  KDD 2005»
16 years 7 months ago
Email data cleaning
Addressed in this paper is the issue of `email data cleaning' for text mining. Many text mining applications need take emails as input. Email data is usually noisy and thus i...
Jie Tang, Hang Li, Yunbo Cao, ZhaoHui Tang
KDD
2004
ACM
163views Data Mining» more  KDD 2004»
16 years 7 months ago
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
William W. Cohen, Sunita Sarawagi
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