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Automatic tagging based on Linked Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F10%3A00504023" target="_blank" >RIV/49777513:23520/10:00504023 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic tagging based on Linked Data

  • Original language description

    We have created a web agent for collecting Call for Papers (CFP) announcements. Our web agent obtains CFP announcements from websites or from mailbox. The most important information is extracted and published on our own special website in a user and machine readable way. One of the most important problems is event classification, categorization and clustering. In this paper we describe unsupervised methods for automatic tagging based on information extraction from Linked data. These methods are usable in situations where we have to tag unknown data and we have no corpus for learning methods. Tagged data can have the form of short messages from RSS, short blog posts or emails. The automatic tags can be used for classifying the conferences. Users can useour web service to search for interesting events and sort them by their own preferences. We obtain tags with their relationship parameters and we can use them for automatic clustering of collected events.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/2C06009" target="_blank" >2C06009: Complex knowledge base tools for natural language communication with the semantic web</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    SOCA´10

  • ISBN

    978-1-4244-9801-7

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    105-108

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Perth Australia

  • Event date

    Dec 13, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article