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    » Constellations and the Unsupervised Learning of Graphs
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    UAI
    2008
    212views Artificial Intelligence» more  UAI 2008»
    Bayesian Out-Trees
    13 years 9 months ago
    Bayesian Out-Trees
    Download  www.cs.columbia.edu
    A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
    Tony Jebara
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    NAACL
    2007
    116views Computational Linguistics» more  NAACL 2007»
    OMS-J: An Opinion Mining System for Japanese Weblog Reviews Using a Combination of Supervised and Unsupervised Approaches
    13 years 9 months ago
    OMS-J: An Opinion Mining System for Japanese Weblog Reviews Using a Combination of Supervised and Unsupervised Approaches
    Download  sig.media.eng.hokudai.ac.jp
    We introduce a simple opinion mining system for analyzing Japanese Weblog reviews called OMS-J. OMS-J is designed to provide an intuitive visual GUI of opinion mining graphs for a...
    Guangwei Wang, Kenji Araki
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    ACL
    2003
    114views Computational Linguistics» more  ACL 2003»
    Unsupervised Learning of Dependency Structure for Language Modeling
    13 years 9 months ago
    Unsupervised Learning of Dependency Structure for Language Modeling
    Download  www.aclweb.org
    This paper presents a dependency language model (DLM) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the r...
    Jianfeng Gao, Hisami Suzuki
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    BIOCOMP
    2007
    111views Bioinformatics» more  BIOCOMP 2007»
    Learning Node Replacement Graph Grammars in Metabolic Pathways
    13 years 9 months ago
    Learning Node Replacement Graph Grammars in Metabolic Pathways
    Download  www.eecs.wsu.edu
    — This paper describes graph-based relational, unsupervised learning algorithm to infer node replacement graph grammar and its application to metabolic pathways. We search for fr...
    Jacek P. Kukluk, Chang Hun You, Lawrence B. Holder...
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    SDM
    2008
    SIAM
    176views Data Mining» more  SDM 2008»
    A General Model for Multiple View Unsupervised Learning
    13 years 9 months ago
    A General Model for Multiple View Unsupervised Learning
    Download  www.cs.binghamton.edu
    Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
    Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
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