Ontology driven data mining and information visualization for the networked home

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    4 Citations (Scopus)

    Abstract

    Data mining is the process of extracting hidden knowledge from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. Visualization is central to data mining. Information visualization is the process of turning abstract data into a visual shape easily understood by the user, making it possible for him/her to generate new knowledge about the relations between the data. Ontologies represent a shared meaning of a domain and they can be used to describe almost any kind of domain concepts explicitly including their terms, attributes, values and relationships facilitating the communication between people and application systems. Leveraging the power of semantic technologies, ontology based data mining and recent trends in information visualization, this work presents the approach towards the management of multi-dimensional often temporal heterogeneous home data. (44 refs.)
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publicationFourth International Conference on Research Challenges in Information Science, RCIS 2010
    Place of PublicationPiscataway, NY, USA
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages147-156
    ISBN (Electronic)978-1-4244-4840-1
    ISBN (Print)978-1-4244-4839-5
    DOIs
    Publication statusPublished - 2010
    MoE publication typeA4 Article in a conference publication
    EventFourth International Conference on Research Challenges in Information Science, RCIS 2010 - Nice, France
    Duration: 19 May 201021 May 2010

    Conference

    ConferenceFourth International Conference on Research Challenges in Information Science, RCIS 2010
    Abbreviated titleRCIS 2010
    CountryFrance
    CityNice
    Period19/05/1021/05/10

    Fingerprint

    Data mining
    Ontology
    Visualization
    Semantics
    Communication

    Keywords

    • Intelligent home
    • data management
    • visualization

    Cite this

    Niskanen, I., & Kantorovitch, J. (2010). Ontology driven data mining and information visualization for the networked home. In Proceedings: Fourth International Conference on Research Challenges in Information Science, RCIS 2010 (pp. 147-156). Piscataway, NY, USA: IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/RCIS.2010.5507374
    Niskanen, Ilkka ; Kantorovitch, Julia. / Ontology driven data mining and information visualization for the networked home. Proceedings: Fourth International Conference on Research Challenges in Information Science, RCIS 2010. Piscataway, NY, USA : IEEE Institute of Electrical and Electronic Engineers , 2010. pp. 147-156
    @inproceedings{dfb89f43c67d42728977ea7b3f5082af,
    title = "Ontology driven data mining and information visualization for the networked home",
    abstract = "Data mining is the process of extracting hidden knowledge from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. Visualization is central to data mining. Information visualization is the process of turning abstract data into a visual shape easily understood by the user, making it possible for him/her to generate new knowledge about the relations between the data. Ontologies represent a shared meaning of a domain and they can be used to describe almost any kind of domain concepts explicitly including their terms, attributes, values and relationships facilitating the communication between people and application systems. Leveraging the power of semantic technologies, ontology based data mining and recent trends in information visualization, this work presents the approach towards the management of multi-dimensional often temporal heterogeneous home data. (44 refs.)",
    keywords = "Intelligent home, data management, visualization",
    author = "Ilkka Niskanen and Julia Kantorovitch",
    year = "2010",
    doi = "10.1109/RCIS.2010.5507374",
    language = "English",
    isbn = "978-1-4244-4839-5",
    pages = "147--156",
    booktitle = "Proceedings",
    publisher = "IEEE Institute of Electrical and Electronic Engineers",
    address = "United States",

    }

    Niskanen, I & Kantorovitch, J 2010, Ontology driven data mining and information visualization for the networked home. in Proceedings: Fourth International Conference on Research Challenges in Information Science, RCIS 2010. IEEE Institute of Electrical and Electronic Engineers , Piscataway, NY, USA, pp. 147-156, Fourth International Conference on Research Challenges in Information Science, RCIS 2010, Nice, France, 19/05/10. https://doi.org/10.1109/RCIS.2010.5507374

    Ontology driven data mining and information visualization for the networked home. / Niskanen, Ilkka; Kantorovitch, Julia.

    Proceedings: Fourth International Conference on Research Challenges in Information Science, RCIS 2010. Piscataway, NY, USA : IEEE Institute of Electrical and Electronic Engineers , 2010. p. 147-156.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    TY - GEN

    T1 - Ontology driven data mining and information visualization for the networked home

    AU - Niskanen, Ilkka

    AU - Kantorovitch, Julia

    PY - 2010

    Y1 - 2010

    N2 - Data mining is the process of extracting hidden knowledge from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. Visualization is central to data mining. Information visualization is the process of turning abstract data into a visual shape easily understood by the user, making it possible for him/her to generate new knowledge about the relations between the data. Ontologies represent a shared meaning of a domain and they can be used to describe almost any kind of domain concepts explicitly including their terms, attributes, values and relationships facilitating the communication between people and application systems. Leveraging the power of semantic technologies, ontology based data mining and recent trends in information visualization, this work presents the approach towards the management of multi-dimensional often temporal heterogeneous home data. (44 refs.)

    AB - Data mining is the process of extracting hidden knowledge from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. Visualization is central to data mining. Information visualization is the process of turning abstract data into a visual shape easily understood by the user, making it possible for him/her to generate new knowledge about the relations between the data. Ontologies represent a shared meaning of a domain and they can be used to describe almost any kind of domain concepts explicitly including their terms, attributes, values and relationships facilitating the communication between people and application systems. Leveraging the power of semantic technologies, ontology based data mining and recent trends in information visualization, this work presents the approach towards the management of multi-dimensional often temporal heterogeneous home data. (44 refs.)

    KW - Intelligent home

    KW - data management

    KW - visualization

    U2 - 10.1109/RCIS.2010.5507374

    DO - 10.1109/RCIS.2010.5507374

    M3 - Conference article in proceedings

    SN - 978-1-4244-4839-5

    SP - 147

    EP - 156

    BT - Proceedings

    PB - IEEE Institute of Electrical and Electronic Engineers

    CY - Piscataway, NY, USA

    ER -

    Niskanen I, Kantorovitch J. Ontology driven data mining and information visualization for the networked home. In Proceedings: Fourth International Conference on Research Challenges in Information Science, RCIS 2010. Piscataway, NY, USA: IEEE Institute of Electrical and Electronic Engineers . 2010. p. 147-156 https://doi.org/10.1109/RCIS.2010.5507374