Taher Zaki

Work place: IRF-SIC Laboratory, Faculty of Science, Ibn Zohr University, Agadir, Morocco

E-mail: t.zaki@uiz.ac.ma


Research Interests: Computer systems and computational processes, Computer Vision, Pattern Recognition, Computer Architecture and Organization, Data Structures and Algorithms, Analysis of Algorithms


Taher Zaki received the PhD degree in Computer Science from the University of Rouen-France and Ibn Zohr University, in 2014, on Systems of information retrieval, text indexing and archive of documents. He is currently on assistant professor at the Ibn Zohr since december 2014, and a researcher of the IRF-SIC laboratory where he integrates the “Document and Learning” group. His main research interests include computer vision, image analysis, pattern recognition, machine learning, and statistical tools for documents modeling and classification, data analysis and clustering. The main applications of these activities concern pattern recognition problems and Arabic text mining and recognition and information extraction from documents.

Author Articles
An Evolutionary Model for Selecting Relevant Textual Features

By Taher Zaki Mohamed Salim EL Bazzi Driss Mammass

DOI: https://doi.org/10.5815/ijmecs.2018.11.06, Pub. Date: 8 Nov. 2018

From a philosophical point of view, the words of a text or a speech are not held just for informational purposes, but they act and react; they have the power to react on their counterparts. Each word, evokes similar or different senses that can influence and interact with the following words, it has a vibratory property. It's not the words themselves that have the impact, but the semantic reaction behind the words. In this context, we propose a new textual data classification approach while trying to imitate human altruistic behavior in order to show the semantic altruistic stakes of natural language words through statistical, semantic and distributional analysis. We present the results of a word extraction method, which combines a distributional proximity index, a selection coefficient and a co-occurrence index with respect to the neighborhood.

[...] Read more.
Other Articles