Dialogue intent identification is an indispensable part of every conversational or a dialogue system. Intent identification is the process of deducing the goal or meaning of the sentence. Intent identification is performed using various classification algorithms. Performance of dialogue systems is vastly dependent on the accuracy of these intent identification methods and algorithms. Thus we review some of the available dialogue intent identification methods, train the classification models on a common dataset and then evaluate on the basis of various performance metrics. A comprehensive comparative study of various intent identification methods is obtained.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Review of Dialogue Intent Identification Methods for Closed Domain Conversational Agents


    Beteiligte:
    Papalkar, Sahil (Autor:in) / Nagmal, Arati (Autor:in) / Karve, Shreya (Autor:in) / Deshpande, S. A. (Autor:in)


    Erscheinungsdatum :

    2018-03-01


    Format / Umfang :

    1497056 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    An LSTM-based Intent Detector for Conversational Recommender Systems

    Jbene, Mourad / Tigani, Smail / Saadane, Rachid et al. | IEEE | 2022


    Intent detection and semantic parsing for navigation dialogue language processing

    Zheng, Yang / Liu, Yongkang / Hansen, John H.L. | IEEE | 2017


    Task flow identification based on user intent

    GRUBER THOMAS ROBERT / CHEYER ADAM JOHN / KITTLAUS DAG et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Task flow identification based on user intent

    GRUBER THOMAS ROBERT / CHEYER ADAM JOHN / KITTLAUS DAG et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Immunizing with information – Inoculation messages against conversational agents’ response failures

    Weiler, Severin / Matt, Christian / Hess, Thomas | Online Contents | 2021

    Freier Zugriff