Search Results for author: Mohamed Ali Hadj Taieb

Found 5 papers, 1 papers with code

Normalized Orthography for Tunisian Arabic

no code implementations20 Feb 2024 Houcemeddine Turki, Kawthar Ellouze, Hager Ben Ammar, Mohamed Ali Hadj Taieb, Imed Adel, Mohamed Ben Aouicha, Pier Luigi Farri, Abderrezak Bennour

Tunisian Arabic (ISO 693-3: aeb) is a distinct linguistic variety native to Tunisia, initially stemmed from the Arabic language and enriched by a multitude of historical influences.

Text Categorization Can Enhance Domain-Agnostic Stopword Extraction

no code implementations24 Jan 2024 Houcemeddine Turki, Naome A. Etori, Mohamed Ali Hadj Taieb, Abdul-Hakeem Omotayo, Chris Chinenye Emezue, Mohamed Ben Aouicha, Ayodele Awokoya, Falalu Ibrahim Lawan, Doreen Nixdorf

This paper investigates the role of text categorization in streamlining stopword extraction in natural language processing (NLP), specifically focusing on nine African languages alongside French.

Text Categorization

A Decade of Scholarly Research on Open Knowledge Graphs

1 code implementation22 Jun 2023 Houcemeddine Turki, Abraham Toluwase Owodunni, Mohamed Ali Hadj Taieb, René Fabrice Bile, Mohamed Ben Aouicha

This paper presents a bibliometric analysis of the scholarly literature on open knowledge graphs published between 2013 and 2023.

Entity Linking graph construction +2

Network representation learning systematic review: ancestors and current development state

no code implementations14 Sep 2021 Amina Amara, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha

In this paper, we present a systematic comprehensive survey of network representation learning, known also as network embedding, from birth to the current development state.

Graph Embedding Network Embedding

Knowledge-Based Construction of Confusion Matrices for Multi-Label Classification Algorithms using Semantic Similarity Measures

no code implementations30 Oct 2020 Houcemeddine Turki, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha

So far, multi-label classification algorithms have been evaluated using statistical methods that do not consider the semantics of the considered classes and that fully depend on abstract computations such as Bayesian Reasoning.

Classification General Classification +3

Cannot find the paper you are looking for? You can Submit a new open access paper.