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    » Mining for Structural Anomalies in Graph-based Data
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    ICDM
    2007
    IEEE
    199views Data Mining» more  ICDM 2007»
    Discovering Structural Anomalies in Graph-Based Data
    13 years 11 months ago
    Discovering Structural Anomalies in Graph-Based Data
    Download  users.csc.tntech.edu
    The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
    William Eberle, Lawrence B. Holder
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    FLAIRS
    2010
    389views Artificial Intelligence» more  FLAIRS 2010»
    Using a Graph-Based Approach for Discovering Cybercrime
    13 years 6 months ago
    Using a Graph-Based Approach for Discovering Cybercrime
    Download  www.eecs.wsu.edu
    The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
    William Eberle, Lawrence B. Holder, Jeffrey Graves
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    DMIN
    2007
    110views Data Mining» more  DMIN 2007»
    Mining for Structural Anomalies in Graph-based Data
    13 years 6 months ago
    Mining for Structural Anomalies in Graph-based Data
    Download  users.csc.tntech.edu
    —In this paper we present graph-based approaches to mining for anomalies in domains where the anomalies consist of unexpected entity/relationship alterations that closely resembl...
    William Eberle, Lawrence B. Holder
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    FLAIRS
    2003
    160views Artificial Intelligence» more  FLAIRS 2003»
    Identifying Inhabitants of an Intelligent Environment Using a Graph-Based Data Mining System
    13 years 5 months ago
    Identifying Inhabitants of an Intelligent Environment Using a Graph-Based Data Mining System
    Download  www.aaai.org
    The goal of the MavHome smart home project is to build an intelligent home environment that is aware of its inhabitants and their activities. Such a home is designed to provide ma...
    Ritesh Mehta, Diane J. Cook, Lawrence B. Holder
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    WSDM
    2012
    ACM
    245views Data Mining» more  WSDM 2012»
    The early bird gets the buzz: detecting anomalies and emerging trends in information networks
    12 years 2 days ago
    The early bird gets the buzz: detecting anomalies and emerging trends in information networks
    Download  paul.rutgers.edu
    In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
    Brian Thompson
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