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    PAKDD
    2009
    ACM
    72views Data Mining» more  PAKDD 2009»
    A Multi-resolution Approach for Atypical Behaviour Mining
    14 years 5 months ago
    A Multi-resolution Approach for Atypical Behaviour Mining
    Download  www-sop.inria.fr
    Atypical behaviours are the basis of a valuable knowledge in domains related to security (e.g. fraud detection for credit card [1], cyber security [4] or safety of critical systems...
    Alice Marascu, Florent Masseglia
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    PAKDD
    2009
    ACM
    135views Data Mining» more  PAKDD 2009»
    On Mining Rating Dependencies in Online Collaborative Rating Networks
    14 years 5 months ago
    On Mining Rating Dependencies in Online Collaborative Rating Networks
    Download  www.cs.sfu.ca
    The trend of social information processing sees e-commerce and social web applications increasingly relying on user-generated content, such as rating, to determine the quality of o...
    Hady Wirawan Lauw, Ee-Peng Lim, Ke Wang
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    IEEEIA
    2009
    155views Intelligent Agents» more  IEEEIA 2009»
    How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent
    13 years 8 months ago
    How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent
    Download  gdac.dinfo.uqam.ca
    In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning a...
    Usef Faghihi, Philippe Fournier-Viger, Roger Nkamb...
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    KDD
    2001
    ACM
    163views Data Mining» more  KDD 2001»
    Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
    14 years 10 months ago
    Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
    Download  www.ailab.si
    During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
    Henrik Boström, Joakim Cöster, Lars Aske...
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    SDM
    2008
    SIAM
    168views Data Mining» more  SDM 2008»
    Semi-Supervised Clustering via Matrix Factorization
    13 years 11 months ago
    Semi-Supervised Clustering via Matrix Factorization
    Download  users.cis.fiu.edu
    The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
    Fei Wang, Tao Li, Changshui Zhang
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