Comparative study of word embedding methods in topic segmentation

Autor: Naili, Marwa, Chaibi, Anja Habacha, Ben Ghezala, Henda Hajjami

Publikováno v: In Procedia Computer Science 2017 112:340-349

Arabic topic identification based on empirical studies of topic models

Autor: Naili, Marwa, Chaibi, Anja, Ghézala, Henda

Publikováno v: Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, INRIA, 2017, Volume 27-2017-Special issue CARI 2016

This paper focuses on the topic identification for the Arabic language based on topic models. We study the Latent Dirichlet Allocation (LDA) as an unsupervised method for the Arabic topic identification. Thus, a deep study of LDA is carried out at tw

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::fd1e78ef2cac9e4cd6d6e0cb31dbee8f
https://arima.episciences.org/3102

Exogenous approach to improve topic segmentation.

Autor: Naili, Marwa, Habacha Chaibi, Anja, Hajjami Ben Ghezala, Henda

Publikováno v: International Journal of Intelligent Computing & Cybernetics; 2016, Vol. 9 Issue 2, p165-178, 14p