Search (3 results, page 1 of 1)

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  1. Euzenat, J.; Shvaiko, P.: Ontology matching (2010) 0.03
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    Date
    20. 6.2012 19:08:22
    Footnote
    Online-Ausg.: Ontology Matching
    LCSH
    Ontologies (Information retrieval)
    Subject
    Ontologies (Information retrieval)
  2. Mauldin, M.L.: Conceptual information retrieval : a case study in adaptive partial parsing (1991) 0.02
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    LCSH
    FERRET (Information retrieval system)
    Information storage and retrieval
    RSWK
    Freitextsuche / Information Retrieval
    Information Retrieval / Expertensystem
    Syntaktische Analyse Information Retrieval
    Subject
    Freitextsuche / Information Retrieval
    Information Retrieval / Expertensystem
    Syntaktische Analyse Information Retrieval
    FERRET (Information retrieval system)
    Information storage and retrieval
  3. Liu, B.: Web data mining : exploring hyperlinks, contents, and usage data (2011) 0.01
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    Abstract
    Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
    Content
    Inhalt: 1. Introduction 2. Association Rules and Sequential Patterns 3. Supervised Learning 4. Unsupervised Learning 5. Partially Supervised Learning 6. Information Retrieval and Web Search 7. Social Network Analysis 8. Web Crawling 9. Structured Data Extraction: Wrapper Generation 10. Information Integration