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    SDM
    2007
    SIAM
    137views Data Mining» more  SDM 2007»
    Semi-supervised Feature Selection via Spectral Analysis
    13 years 6 months ago
    Semi-supervised Feature Selection via Spectral Analysis
    Download  www.public.asu.edu
    Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
    Zheng Zhao, Huan Liu
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    TRECVID
    2008
    143views Internet Technology» more  TRECVID 2008»
    PicSOM Experiments in TRECVID 2008
    13 years 6 months ago
    PicSOM Experiments in TRECVID 2008
    Download  www-nlpir.nist.gov
    Our experiments in TRECVID 2008 include participation in the high-level feature extraction, automatic search, video summarization, and video copy detection tasks, using a common s...
    Markus Koskela, Mats Sjöberg, Ville Viitaniem...
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    SPLC
    2008
    115views Software Engineering» more  SPLC 2008»
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    13 years 6 months ago
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    Download  www.dre.vanderbilt.edu
    Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
    Jules White, B. Doughtery, Douglas C. Schmidt
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    NIPS
    2007
    201views Information Technology» more  NIPS 2007»
    Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
    13 years 6 months ago
    Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
    Download  books.nips.cc
    We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
    Maryam Mahdaviani, Tanzeem Choudhury
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    NAACL
    2007
    75views Computational Linguistics» more  NAACL 2007»
    A Systematic Exploration of the Feature Space for Relation Extraction
    13 years 6 months ago
    A Systematic Exploration of the Feature Space for Relation Extraction
    Download  sifaka.cs.uiuc.edu
    Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
    Jing Jiang, ChengXiang Zhai
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    SEBD
    2008
    177views Database» more  SEBD 2008»
    Using PageRank in Feature Selection
    13 years 6 months ago
    Using PageRank in Feature Selection
    Download  www.di.unito.it
    Abstract. Feature selection is an important task in data mining because it allows to reduce the data dimensionality and eliminates the noisy variables. Traditionally, feature selec...
    Dino Ienco, Rosa Meo, Marco Botta
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    SEBD
    2008
    169views Database» more  SEBD 2008»
    Clustering the Feature Space
    13 years 6 months ago
    Clustering the Feature Space
    Download  www.di.unito.it
    Abstract Dino Ienco and Rosa Meo Dipartimento di Informatica, Universit`a di Torino, Italy In this paper we propose and test the use of hierarchical clustering for feature selectio...
    Dino Ienco, Rosa Meo
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    SDM
    2008
    SIAM
    136views Data Mining» more  SDM 2008»
    Exploration and Reduction of the Feature Space by Hierarchical Clustering
    13 years 6 months ago
    Exploration and Reduction of the Feature Space by Hierarchical Clustering
    Download  www.di.unito.it
    In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
    Dino Ienco, Rosa Meo
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    SDM
    2008
    SIAM
    117views Data Mining» more  SDM 2008»
    A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
    13 years 6 months ago
    A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
    Download  vk.cs.umn.edu
    With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
    Yijun Sun, Sinisa Todorovic, Steve Goodison
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    SCAI
    2008
    235views Artificial Intelligence» more  SCAI 2008»
    Defect Prediction in Hot Strip Rolling Using ANN and SVM
    13 years 6 months ago
    Defect Prediction in Hot Strip Rolling Using ANN and SVM
    Download  www.ee.oulu.fi
    One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
    Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...
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