Combining topic-based model and text categorisation approach for utterance understanding in human-machine dialogue
by Mohamed Lichouri; Rachida Djeradi; Amar Djeradi
International Journal of Computational Science and Engineering (IJCSE), Vol. 17, No. 1, 2018

Abstract: In the present paper, we suggest an implementation of an automatic understanding system of the statement in human-machine communication. The architecture we adopt is based on a stochastic approach that assumes that the understanding of a statement is nothing but a simple theme identification process. Therefore, we present a new theme identification method based on a documentary retrieval technique which is text (document) classification (Bawakid and Oussalah, 2010). The method we suggest was validated on a basic platform that gives information related to university schooling management (querying a student database), taking into consideration a textual input in French. This method has achieved a theme identification rate of 95% and a correct utterance understanding rate of about 91.66%.

Online publication date: Mon, 03-Sep-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com