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Introduction

Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from data, often based on underlying large data sets. A major aspect of Knowledge Discovery is data mining, i.e. applying data analysis and discovery algorithms that produce a particular enumeration of patterns (or models) over the data. Knowledge Discovery also includes the evaluation of patterns and identification of which add to knowledge. Information retrieval (IR) is concerned with gathering relevant information from unstructured and semantically fuzzy data in texts and other media, searching for information within documents and for metadata about documents, as well as searching relational databases and the Web. Automation of information retrieval enables the reduction of what has been called "information overload". Information retrieval can be combined with knowledge discovery to create software tools that empower users of decision support systems to better understand and use the knowledge underlying large data sets.

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Submission Topics

CONFERENCE TOPICS Web mining Machine Learning Foundations of knowledge discovery in databases Data Analytics Data mining in electronic commerce Interactive and online data mining Process mining Integration of data warehousing and data mining Data reductio
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Important Date
  • Conference Date

    Sep 19

    2013

    to

    Sep 22

    2013

  • Sep 22 2013

    Registration deadline

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Institute for Systems and Technologies of Information Control and Communication
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