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» Unsupervised feature selection using a neuro-fuzzy approach
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KDD
2006
ACM
150views Data Mining» more  KDD 2006»
14 years 9 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
GFKL
2007
Springer
202views Data Mining» more  GFKL 2007»
14 years 20 days ago
Collective Classification for Labeling of Places and Objects in 2D and 3D Range Data
In this paper, we present an algorithm to identify types of places and objects from 2D and 3D laser range data obtained in indoor environments. Our approach is a combination of a c...
Rudolph Triebel, Óscar Martínez Mozo...
BMCBI
2004
114views more  BMCBI 2004»
13 years 8 months ago
Profiled support vector machines for antisense oligonucleotide efficacy prediction
Background: This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises ...
Gustavo Camps-Valls, Alistair M. Chalk, Antonio J....
EMNLP
2007
13 years 10 months ago
What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA
This paper presents a syntax-driven approach to question answering, specifically the answer-sentence selection problem for short-answer questions. Rather than using syntactic fea...
Mengqiu Wang, Noah A. Smith, Teruko Mitamura
LREC
2008
118views Education» more  LREC 2008»
13 years 10 months ago
A Flexible Wizard of Oz Environment for Rapid Prototyping
This paper presents a freely available, and flexible Wizard of Oz environment for rapid prototyping. The system is designed to investigate the required features of a dialog system...
Stefan Scherer, Petra-Maria Strauß