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: Managing and Mining Uncertain Data
  name:
    name part: Aggarwal, Charu C.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXII, 494 p. 60 illus. online resource.
  abstract: Managing and Mining Uncertain Data contains surveys by well known researchers in the field of uncertain databases. The book presents the most recent models, algorithms, and applications in the uncertain data field in a structured and concise way. This book is organized so as to cover the most important management and mining topics in the field. The idea is to make it accessible not only to researchers, but also to application-driven practitioners for solving real problems. Given the lack of structurally organized information on the new and emerging area of uncertain data, this book provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level database students in computer science and engineering. Editor Biography Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 120 papers in major conferences and journals in the database and data mining field. He has applied for or been granted over 65 US and International patents, and has thrice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 17 invention achievement awards by IBM for his patents. His work on real time bio-terrorist threat detection in data streams won the IBM Corporate award for Environmental Excellence in 2003. He is a recipient of the IBM Outstanding Innovation Award in 2008 for his scientific contributions to privacy technology, and a recipient of the IBM Research Division award for his contributions to stream mining for the System S project. He has served on the program committee of most major database conferences, and was program chair for the Data Mining and Knowledge Discovery Workshop, 2003, and program vice-chairs for th…
  table of contents: An Introduction to Uncertain Data Algorithms and Applications -- Models for Incomplete and Probabilistic Information -- Relational Models and Algebra for Uncertain Data -- Graphical Models for Uncertain Data -- Trio A System for Data Uncertainty and Lineage -- MayBMS A System for Managing Large Probabilistic Databases -- Uncertainty in Data Integration -- Sketching Aggregates over Probabilistic Streams -- Probabilistic Join Queries in Uncertain Databases -- Indexing Uncertain Data -- Querying Uncertain Spatiotemporal Data -- Probabilistic XML -- On Clustering Algorithms for Uncertain Data -- On Applications of Density Transforms for Uncertain Data Mining -- Frequent Pattern Mining Algorithms with Uncertain Data -- Probabilistic Querying and Mining of Biological Images.
  note: edited by Charu C. Aggarwal.
  subject:
    topic: Computer science
  subject:
    topic: Computer security
  subject:
    topic: Database management
  subject:
    topic: Data mining
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Database Management
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Systems and Data Security
  subject:
    topic: Information Systems Applications (incl. Internet)
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Database Systems, 35
  identifier: 9780387096902
  identifier: http://dx.doi.org/10.1007/978-0-387-09690-2
  record info:
    record creation date: 100708
    record change date: 20151204162316.0
    record identifier: 978-0-387-09690-2