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    KDD
    2009
    ACM
    172views Data Mining» more  KDD 2009»
    Towards combining web classification and web information extraction: a case study
    14 years 5 months ago
    Towards combining web classification and web information extraction: a case study
    Download  www.hpl.hp.com
    : ? Towards Combining Web Classification and Web Information Extraction: a Case Study Ping Luo, Fen Lin, Yuhong Xiong, Yong Zhao, Zhongzhi Shi HP Laboratories HPL-2009-86 Classific...
    Ping Luo, Fen Lin, Yuhong Xiong, Yong Zhao, Zhongz...
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    KDD
    2009
    ACM
    215views Data Mining» more  KDD 2009»
    Large-scale sparse logistic regression
    14 years 5 months ago
    Large-scale sparse logistic regression
    Download  www.public.asu.edu
    Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Spa...
    Jun Liu, Jianhui Chen, Jieping Ye
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    KDD
    2009
    ACM
    156views Data Mining» more  KDD 2009»
    Turning down the noise in the blogosphere
    14 years 5 months ago
    Turning down the noise in the blogosphere
    Download  select.cs.cmu.edu
    In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guidin...
    Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos...
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    KDD
    2009
    ACM
    180views Data Mining» more  KDD 2009»
    Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
    14 years 5 months ago
    Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
    Download  www.research.rutgers.edu
    Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
    Sofus A. Macskassy
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    KDD
    2009
    ACM
    185views Data Mining» more  KDD 2009»
    On compressing social networks
    14 years 5 months ago
    On compressing social networks
    Download  www.eecs.harvard.edu
    Motivated by structural properties of the Web graph that support efficient data structures for in memory adjacency queries, we study the extent to which a large network can be com...
    Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, ...
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    KDD
    2009
    ACM
    150views Data Mining» more  KDD 2009»
    Large human communication networks: patterns and a utility-driven generator
    14 years 5 months ago
    Large human communication networks: patterns and a utility-driven generator
    Download  www.cs.cmu.edu
    Given a real, and weighted person-to-person network which changes over time, what can we say about the cliques that it contains? Do the incidents of communication, or weights on t...
    Nan Du, Christos Faloutsos, Bai Wang, Leman Akoglu
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    KDD
    2009
    ACM
    204views Data Mining» more  KDD 2009»
    Improving classification accuracy using automatically extracted training data
    14 years 5 months ago
    Improving classification accuracy using automatically extracted training data
    Download  pages.cs.wisc.edu
    Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
    Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...
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    KDD
    2009
    ACM
    163views Data Mining» more  KDD 2009»
    Large-scale graph mining using backbone refinement classes
    14 years 5 months ago
    Large-scale graph mining using backbone refinement classes
    Download  www.maunz.de
    We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...
    Andreas Maunz, Christoph Helma, Stefan Kramer
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    KDD
    2009
    ACM
    178views Data Mining» more  KDD 2009»
    Constrained optimization for validation-guided conditional random field learning
    14 years 5 months ago
    Constrained optimization for validation-guided conditional random field learning
    Download  www.cse.wustl.edu
    Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
    Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
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    KDD
    2009
    ACM
    305views Data Mining» more  KDD 2009»
    Grocery shopping recommendations based on basket-sensitive random walk
    14 years 5 months ago
    Grocery shopping recommendations based on basket-sensitive random walk
    Download  www-ai.cs.uni-dortmund.de
    We describe a recommender system in the domain of grocery shopping. While recommender systems have been widely studied, this is mostly in relation to leisure products (e.g. movies...
    Ming Li, M. Benjamin Dias, Ian H. Jarman, Wael El-...
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