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: Advances in Social Network Mining and Analysis
    sub title: Second International Workshop, SNAKDD 2008, Las Vegas, NV, USA, August 24-27, 2008
  name:
    name part: Giles, Lee.
    role:
      role term: editor.
  name:
    name part: Smith, Marc.
    role:
      role term: editor.
  name:
    name part: Yen, John.
    role:
      role term: editor.
  name:
    name part: Zhang, Haizheng.
    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: XI, 131 p. 47 illus. online resource.
  abstract: This year’s volume of Advances in Social Network Analysis contains the p- ceedings for the Second International Workshop on Social Network Analysis (SNAKDD 2008). The annual workshop co-locates with the ACM SIGKDD - ternational Conference on Knowledge Discovery and Data Mining (KDD). The second SNAKDD workshop was held with KDD 2008 and received more than 32 submissions on social network mining and analysis topics. We accepted 11 regular papers and 8 short papers. Seven of the papers are included in this volume. In recent years, social network research has advanced signi?cantly, thanks to the prevalence of the online social websites and instant messaging systems as well as the availability of a variety of large-scale o?ine social network systems. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Researchers are - creasingly interested in addressing a wide range of challenges residing in these disparate social network systems, including identifying common static topol- ical properties and dynamic properties during the formation and evolution of these social networks, and how contextual information can help in analyzing the pertaining socialnetworks.These issues haveimportant implications oncom- nitydiscovery,anomalydetection,trendpredictionandcanenhanceapplications in multiple domains such as information retrieval, recommendation systems, - curity and so on.
  table of contents: Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study -- Community Detection Using a Measure of Global Influence -- Communication Dynamics of Blog Networks -- Finding Spread Blockers in Dynamic Networks -- Social Network Mining with Nonparametric Relational Models -- Using Friendship Ties and Family Circles for Link Prediction -- Information Theoretic Criteria for Community Detection.
  note: edited by Lee Giles, Marc Smith, John Yen, Haizheng Zhang.
  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: Information Systems Applications (incl. Internet)
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Database Management
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Computer Communication Networks
  classification: QA76.76.A65
  classification: 005.7
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 5498
  identifier: 9783642149290
  identifier: http://dx.doi.org/10.1007/978-3-642-14929-0
  record info:
    record creation date: 100808
    record change date: 20151204174715.0
    record identifier: 978-3-642-14929-0