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    EDM
    2009
    107views Data Mining» more  EDM 2009»
    Differences Between Intelligent Tutor Lessons, and the Choice to Go Off-Task
    13 years 8 months ago
    Differences Between Intelligent Tutor Lessons, and the Choice to Go Off-Task
    Download  www.educationaldatamining.org
    Recent research has suggested that differences between intelligent tutor lessons predict a large amount of the variance in the prevalence of gaming the system [4]. Within this pape...
    Ryan Baker
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    VLDB
    1999
    ACM
    107views Database» more  VLDB 1999»
    The Value of Merge-Join and Hash-Join in SQL Server
    14 years 2 months ago
    The Value of Merge-Join and Hash-Join in SQL Server
    Download  www.vldb.org
    Microsoft SQL Server was successful for many years for transaction processing and decision support workloads with neither merge join nor hash join, relying entirely on nested loop...
    Goetz Graefe
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    KDD
    2009
    ACM
    132views Data Mining» more  KDD 2009»
    Learning patterns in the dynamics of biological networks
    14 years 10 months ago
    Learning patterns in the dynamics of biological networks
    Download  www-ai.cs.uni-dortmund.de
    Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
    Chang Hun You, Lawrence B. Holder, Diane J. Cook
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    KDD
    2008
    ACM
    232views Data Mining» more  KDD 2008»
    Anticipating annotations and emerging trends in biomedical literature
    14 years 10 months ago
    Anticipating annotations and emerging trends in biomedical literature
    Download  www.mybytes.de
    The BioJournalMonitor is a decision support system for the analysis of trends and topics in the biomedical literature. Its main goal is to identify potential diagnostic and therap...
    Bernd Wachmann, Dmitriy Fradkin, Fabian Mörch...
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    KDD
    2008
    ACM
    137views Data Mining» more  KDD 2008»
    Learning classifiers from only positive and unlabeled data
    14 years 10 months ago
    Learning classifiers from only positive and unlabeled data
    Download  cseweb.ucsd.edu
    The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
    Charles Elkan, Keith Noto
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