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Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F17%3A43910950" target="_blank" >RIV/62156489:43110/17:43910950 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.4018/978-1-5225-1759-7.ch081" target="_blank" >http://dx.doi.org/10.4018/978-1-5225-1759-7.ch081</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4018/978-1-5225-1759-7.ch081" target="_blank" >10.4018/978-1-5225-1759-7.ch081</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities

  • Original language description

    The chapter introduces clustering as a family of algorithms that can be successfully used to organize text documents into groups without prior knowledge of these groups. The chapter also demonstrates using unsupervised clustering to group large amount of unlabeled textual data (customer reviews written informally in five natural languages) so it can be used later for further analysis. The attention is paid to the process of selecting clustering algorithms, their parameters, methods of data preprocessing, and to the methods of evaluating the results by a human expert with an assistance of computers, too. The feasibility has been demonstrated by a number of experiments with external evaluation using known labels and expert validation with an assistance of a computer. It has been found that it is possible to apply the same procedures, including clustering, cluster validation, and detection of topics and significant words for different natural languages with satisfactory results.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Book/collection name

    Artificial Intelligence: Concepts, Methodologies, Tools, and Applications

  • ISBN

    978-1-5225-1759-7

  • Number of pages of the result

    40

  • Pages from-to

    1981-2020

  • Number of pages of the book

    3048

  • Publisher name

    IGI Global

  • Place of publication

    Hershey

  • UT code for WoS chapter