rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advanced Data Mining and Applications
    sub title: 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II
  name:
    name part: Cao, Longbing.
    role:
      role term: editor.
  name:
    name part: Zhong, Jiang.
    role:
      role term: editor.
  name:
    name part: Feng, Yong.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 576 p. 198 illus. online resource.
  abstract: With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
  table of contents: III Data Mining Methodologies and Processes -- Incremental Learning by Heterogeneous Bagging Ensemble -- CPLDP: An Efficient Large Dataset Processing System Built on Cloud Platform -- A General Multi-relational Classification Approach Using Feature Generation and Selection -- A Unified Approach to the Extraction of Rules from Artificial Neural Networks and Support Vector Machines -- A Clustering-Based Data Reduction for Very Large Spatio-Temporal Datasets -- Change a Sequence into a Fuzzy Number -- Multiple Kernel Learning Improved by MMD -- A Refinement Approach to Handling Model Misfit in Semi-supervised Learning -- Soft Set Approach for Selecting Decision Attribute in Data Clustering -- Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study -- Adapt the mRMR Criterion for Unsupervised Feature Selection -- Evaluating the Distance between Two Uncertain Categorical Objects -- Construction Cosine Radial Basic Function Neural Networks Based on Artificial Immune Networks -- Spatial Filter Selection with LASSO for EEG Classification -- Boolean Algebra and Compression Technique for Association Rule Mining -- Cluster Based Symbolic Representation and Feature Selection for Text Classification -- SimRate: Improve Collaborative Recommendation Based on Rating Graph for Sparsity -- Logistic Regression for Transductive Transfer Learning from Multiple Sources -- Double Table Switch: An Efficient Partitioning Algorithm for Bottom-Up Computation of Data Cubes -- IV Data Mining Applications and Systems -- Tag Recommendation Based on Bayesian Principle -- Comparison of Different Methods to Fuse Theos Images -- Using Genetic K-Means Algorithm for PCA Regression Data in Customer Churn Prediction -- Time-Constrained Test Selection for Regression Testing -- Chinese New Word Detection from Query Logs -- Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization -- Topic-Based User Segmentation for Online Advertising with Latent Dirichlet Allocation -- Applying…
  note: edited by Longbing Cao, Jiang Zhong, Yong Feng.
  subject:
    topic: Computer science
  subject:
    topic: Computer communication systems
  subject:
    topic: Database management
  subject:
    topic: Data mining
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Database Management
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Computer Communication Networks
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 6441
  identifier: 9783642173134
  identifier: http://dx.doi.org/10.1007/978-3-642-17313-4
  record info:
    record creation date: 101117
    record change date: 20151204152908.0
    record identifier: 978-3-642-17313-4