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CLEF
2010
Springer
11 years 7 months ago
Web Person Name Disambiguation by Relevance Weighting of Extended Feature Sets
Abstract. This paper describes our approach to the Person Name Disambiguation clustering task in the Third Web People Search Evaluation Campaign(WePS3). The method focuses on two a...
Chong Long, Lei Shi
SSWMC
2004
11 years 8 months ago
Universal image steganalysis using rate-distortion curves
The goal of image steganography is to embed information in a cover image using modifications that are undetectable. In actual practice, however, most techniques produce stego imag...
Mehmet Utku Celik, Gaurav Sharma, A. Murat Tekalp
FIW
2003
106views Communications» more  FIW 2003»
11 years 8 months ago
Context and Intent in Call Processing
A new feature set suited for IP telephony is described. The user value of this feature set is discussed in terms of social science results. This feature set supports natural human ...
Tom Gray, Ramiro Liscano, Barry Wellman, Anabel Qu...
CICLING
2008
Springer
11 years 8 months ago
Verb Class Discovery from Rich Syntactic Data
Abstract. Previous research has shown that syntactic features are the most informative features in automatic verb classification. We investigate their optimal characteristics by co...
Lin Sun, Anna Korhonen, Yuval Krymolowski
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
11 years 11 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
ISMIR
2004
Springer
113views Music» more  ISMIR 2004»
11 years 12 months ago
Audio Features for Noisy Sound Segmentation
Automatic audio classification usually considers sounds as music, speech, silence or noise, but works about the noise class are rare. Audio features are generally specific to sp...
Pierre Hanna, Nicolas Louis, Myriam Desainte-Cathe...
ILP
2004
Springer
11 years 12 months ago
First Order Random Forests with Complex Aggregates
Random forest induction is a bagging method that randomly samples the feature set at each node in a decision tree. In propositional learning, the method has been shown to work well...
Celine Vens, Anneleen Van Assche, Hendrik Blockeel...
IFIP
2005
Springer
12 years 2 days ago
Content-Based Image Retrieval for Digital Forensics
Digital forensic investigators are often faced with the task of manually examining a large number of (photographic) images in order to identify potential evidence. The task can be...
Yixin Chen, Vassil Roussev, Golden G. Richard III,...
ICMCS
2006
IEEE
162views Multimedia» more  ICMCS 2006»
12 years 18 days ago
Musical Signal Type Discrimination based on Large Open Feature Sets
Automatic discrimination of musical signal types as speech, singing, music, genres or drumbeats within audio streams is of great importance e.g. for radio broadcast stream segment...
Björn Schuller, Frank Wallhoff, Dejan Arsic, ...
ECML
2007
Springer
12 years 22 days ago
Optimizing Feature Sets for Structured Data
Choosing a suitable feature representation for structured data is a non-trivial task due to the vast number of potential candidates. Ideally, one would like to pick a small, but in...
Ulrich Rückert, Stefan Kramer
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