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    KDD
    2009
    ACM
    245views Data Mining» more  KDD 2009»
    Mining rich session context to improve web search
    14 years 5 months ago
    Mining rich session context to improve web search
    Download  www.cc.gatech.edu
    User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
    Guangyu Zhu, Gilad Mishne
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    KDD
    2009
    ACM
    232views Data Mining» more  KDD 2009»
    Classification of software behaviors for failure detection: a discriminative pattern mining approach
    14 years 5 months ago
    Classification of software behaviors for failure detection: a discriminative pattern mining approach
    Download  www.cs.uiuc.edu
    Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
    David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
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    KDD
    2009
    ACM
    190views Data Mining» more  KDD 2009»
    Efficient influence maximization in social networks
    14 years 5 months ago
    Efficient influence maximization in social networks
    Download  research.microsoft.com
    Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. In this paper, we study the ...
    Wei Chen, Yajun Wang, Siyu Yang
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    KDD
    2009
    ACM
    178views Data Mining» more  KDD 2009»
    Catching the drift: learning broad matches from clickthrough data
    14 years 5 months ago
    Catching the drift: learning broad matches from clickthrough data
    Download  research.microsoft.com
    Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
    Sonal Gupta, Mikhail Bilenko, Matthew Richardson
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    KDD
    2009
    ACM
    322views Data Mining» more  KDD 2009»
    Mining for the most certain predictions from dyadic data
    14 years 5 months ago
    Mining for the most certain predictions from dyadic data
    Download  velblod.videolectures.net
    Meghana Deodhar, Joydeep Ghosh
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    KDD
    2009
    ACM
    187views Data Mining» more  KDD 2009»
    New ensemble methods for evolving data streams
    14 years 5 months ago
    New ensemble methods for evolving data streams
    Download  www.lsi.upc.edu
    Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such...
    Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes...
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    KDD
    2009
    ACM
    190views Data Mining» more  KDD 2009»
    Named entity mining from click-through data using weakly supervised latent dirichlet allocation
    14 years 5 months ago
    Named entity mining from click-through data using weakly supervised latent dirichlet allocation
    Download  research.microsoft.com
    This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
    Gu Xu, Shuang-Hong Yang, Hang Li
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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 5 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
    191views Data Mining» more  KDD 2009»
    Efficient methods for topic model inference on streaming document collections
    14 years 5 months ago
    Efficient methods for topic model inference on streaming document collections
    Download  www.cs.umass.edu
    Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
    Limin Yao, David M. Mimno, Andrew McCallum
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    KDD
    2009
    ACM
    193views Data Mining» more  KDD 2009»
    Probabilistic frequent itemset mining in uncertain databases
    14 years 5 months ago
    Probabilistic frequent itemset mining in uncertain databases
    Download  www.dbs.informatik.uni-muenchen.de
    Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
    Andreas Züfle, Florian Verhein, Hans-Peter Kr...
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