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 I
  name:
    name part: Cao, Longbing.
    role:
      role term: editor.
  name:
    name part: Feng, Yong.
    role:
      role term: editor.
  name:
    name part: Zhong, Jiang.
    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, 628 p. 221 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: Data Mining Foundations -- Cost Sensitive Classification in Data Mining -- Web Users Access Paths Clustering Based on Possibilistic and Fuzzy Sets Theory -- Discriminative Markov Logic Network Structure Learning Based on Propositionalization and ? 2-Test -- EWGen: Automatic Generation of Item Weights for Weighted Association Rule Mining -- Best Clustering Configuration Metrics: Towards Multiagent Based Clustering -- On Probabilistic Models for Uncertain Sequential Pattern Mining -- Cube Based Summaries of Large Association Rule Sets -- A Perceptron-Like Linear Supervised Algorithm for Text Classification -- Research on Time Series Forecasting Model Based on Moore Automata -- A Clustering Algorithm FCM-ACO for Supplier Base Management -- Nearest Neighbour Distance Matrix Classification -- Classification Inductive Rule Learning with Negated Features -- Fast Retrieval of Time Series Using a Multi-resolution Filter with Multiple Reduced Spaces -- DHPTID-HYBRID Algorithm: A Hybrid Algorithm for Association Rule Mining -- An Improved Rough Clustering Using Discernibility Based Initial Seed Computation -- Fixing the Threshold for Effective Detection of Near Duplicate Web Documents in Web Crawling -- Topic-Constrained Hierarchical Clustering for Document Datasets -- Discretization of Time Series Dataset Using Relative Frequency and K-Nearest Neighbor Approach -- MSDBSCAN: Multi-density Scale-Independent Clustering Algorithm Based on DBSCAN -- An Efficient Algorithm for Mining Erasable Itemsets -- Discord Region Based Analysis to Improve Data Utility of Privately Published Time Series -- Deep Web Sources Classifier Based on DSOM-EACO Clustering Model -- Kernel Based K-Medoids for Clustering Data with Uncertainty -- Frequent Pattern Mining Using Modified CP-Tree for Knowledge Discovery -- Spatial Neighborhood Clustering Based on Data Field -- Surrounding Influenced K-Nearest Neighbors: A New Distance Based Classifier -- A Centroid k-Nearest Neighbor Method -- Mining Spatial A…
  note: edited by Longbing Cao, Yong Feng, Jiang Zhong.
  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: Computer Communication Networks
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Database Management
  subject:
    topic: Data Mining and Knowledge Discovery
  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, 6440
  identifier: 9783642173165
  identifier: http://dx.doi.org/10.1007/978-3-642-17316-5
  record info:
    record creation date: 101117
    record change date: 20151204152908.0
    record identifier: 978-3-642-17316-5