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    KDD
    2009
    ACM
    206views Data Mining» more  KDD 2009»
    Ranking-based clustering of heterogeneous information networks with star network schema
    14 years 10 months ago
    Ranking-based clustering of heterogeneous information networks with star network schema
    Download  www.cs.uiuc.edu
    A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden s...
    Yizhou Sun, Yintao Yu, Jiawei Han
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    KDD
    2009
    ACM
    198views Data Mining» more  KDD 2009»
    Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
    14 years 10 months ago
    Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
    Download  www.pervasivedatarush.com
    All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
    Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
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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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    MOBISYS
    2009
    ACM
    182views Computer Networks» more  MOBISYS 2009»
    Predictive methods for improved vehicular WiFi access
    14 years 10 months ago
    Predictive methods for improved vehicular WiFi access
    Download  www.wings.cs.sunysb.edu
    With the proliferation of WiFi technology, many WiFi networks are accessible from vehicles on the road making vehicular WiFi access realistic. However, several challenges exist: l...
    Pralhad Deshpande, Anand Kashyap, Chul Sung, Samir...
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    KDD
    2008
    ACM
    159views Data Mining» more  KDD 2008»
    Semi-supervised learning with data calibration for long-term time series forecasting
    14 years 10 months ago
    Semi-supervised learning with data calibration for long-term time series forecasting
    Download  www.cse.msu.edu
    Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
    Haibin Cheng, Pang-Ning Tan
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