Semantic index assignment

Basak Guler, Aylin Yener

    Research output: Contribution to conferencePaper

    2 Citations (Scopus)

    Abstract

    Conventional performance criteria for communication networks do not take into account the semantics of the data to be communicated. For example, (word) error rates treat errors between semantically similar words (car and automobile) and semantically distant words (car and computer) equally. In reality, the meaning of the message is distorted much less when automobile is recovered instead of computer when the intended message is car. In order to correctly address the performance of a semantic system, a new performance criterion is necessary that takes into account the semantic similarities between recovered words. We study in this paper the index assignment problem with a source that produces semantic messages to develop a better understanding of how their meanings affect the semantic error performance in a noisy communication network, and in particular for networks with queries. To this end, we utilize the semantic distances based on lexical taxonomies as a distortion measure in a communication system. Our findings indicate the need for development of semantics-aware physical systems that allow for better integration of human factors and intelligence within complex systems design.

    Original languageEnglish (US)
    Pages431-436
    Number of pages6
    DOIs
    StatePublished - Jan 1 2014
    Event2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014 - Budapest, Hungary
    Duration: Mar 24 2014Mar 28 2014

    Other

    Other2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014
    CountryHungary
    CityBudapest
    Period3/24/143/28/14

    Fingerprint

    Semantics
    Railroad cars
    Automobiles
    Telecommunication networks
    Taxonomies
    Human engineering
    Large scale systems
    Communication systems
    Systems analysis

    All Science Journal Classification (ASJC) codes

    • Software

    Cite this

    Guler, B., & Yener, A. (2014). Semantic index assignment. 431-436. Paper presented at 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, Budapest, Hungary. https://doi.org/10.1109/PerComW.2014.6815245
    Guler, Basak ; Yener, Aylin. / Semantic index assignment. Paper presented at 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, Budapest, Hungary.6 p.
    @conference{9d3e806e8d844a11bd02eb5686fae7a5,
    title = "Semantic index assignment",
    abstract = "Conventional performance criteria for communication networks do not take into account the semantics of the data to be communicated. For example, (word) error rates treat errors between semantically similar words (car and automobile) and semantically distant words (car and computer) equally. In reality, the meaning of the message is distorted much less when automobile is recovered instead of computer when the intended message is car. In order to correctly address the performance of a semantic system, a new performance criterion is necessary that takes into account the semantic similarities between recovered words. We study in this paper the index assignment problem with a source that produces semantic messages to develop a better understanding of how their meanings affect the semantic error performance in a noisy communication network, and in particular for networks with queries. To this end, we utilize the semantic distances based on lexical taxonomies as a distortion measure in a communication system. Our findings indicate the need for development of semantics-aware physical systems that allow for better integration of human factors and intelligence within complex systems design.",
    author = "Basak Guler and Aylin Yener",
    year = "2014",
    month = "1",
    day = "1",
    doi = "10.1109/PerComW.2014.6815245",
    language = "English (US)",
    pages = "431--436",
    note = "2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014 ; Conference date: 24-03-2014 Through 28-03-2014",

    }

    Guler, B & Yener, A 2014, 'Semantic index assignment', Paper presented at 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, Budapest, Hungary, 3/24/14 - 3/28/14 pp. 431-436. https://doi.org/10.1109/PerComW.2014.6815245

    Semantic index assignment. / Guler, Basak; Yener, Aylin.

    2014. 431-436 Paper presented at 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, Budapest, Hungary.

    Research output: Contribution to conferencePaper

    TY - CONF

    T1 - Semantic index assignment

    AU - Guler, Basak

    AU - Yener, Aylin

    PY - 2014/1/1

    Y1 - 2014/1/1

    N2 - Conventional performance criteria for communication networks do not take into account the semantics of the data to be communicated. For example, (word) error rates treat errors between semantically similar words (car and automobile) and semantically distant words (car and computer) equally. In reality, the meaning of the message is distorted much less when automobile is recovered instead of computer when the intended message is car. In order to correctly address the performance of a semantic system, a new performance criterion is necessary that takes into account the semantic similarities between recovered words. We study in this paper the index assignment problem with a source that produces semantic messages to develop a better understanding of how their meanings affect the semantic error performance in a noisy communication network, and in particular for networks with queries. To this end, we utilize the semantic distances based on lexical taxonomies as a distortion measure in a communication system. Our findings indicate the need for development of semantics-aware physical systems that allow for better integration of human factors and intelligence within complex systems design.

    AB - Conventional performance criteria for communication networks do not take into account the semantics of the data to be communicated. For example, (word) error rates treat errors between semantically similar words (car and automobile) and semantically distant words (car and computer) equally. In reality, the meaning of the message is distorted much less when automobile is recovered instead of computer when the intended message is car. In order to correctly address the performance of a semantic system, a new performance criterion is necessary that takes into account the semantic similarities between recovered words. We study in this paper the index assignment problem with a source that produces semantic messages to develop a better understanding of how their meanings affect the semantic error performance in a noisy communication network, and in particular for networks with queries. To this end, we utilize the semantic distances based on lexical taxonomies as a distortion measure in a communication system. Our findings indicate the need for development of semantics-aware physical systems that allow for better integration of human factors and intelligence within complex systems design.

    UR - http://www.scopus.com/inward/record.url?scp=84901309462&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84901309462&partnerID=8YFLogxK

    U2 - 10.1109/PerComW.2014.6815245

    DO - 10.1109/PerComW.2014.6815245

    M3 - Paper

    AN - SCOPUS:84901309462

    SP - 431

    EP - 436

    ER -

    Guler B, Yener A. Semantic index assignment. 2014. Paper presented at 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, PERCOM WORKSHOPS 2014, Budapest, Hungary. https://doi.org/10.1109/PerComW.2014.6815245