Farek Lazhar

Orcid: 0000-0002-6958-736X

According to our database1, Farek Lazhar authored at least 14 papers between 2016 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Transformer-vae for contextual anomaly detection in text.
Int. J. Mach. Learn. Cybern., April, 2026

A randomized block-based SVD image watermarking technique for IoT applications.
Multim. Tools Appl., January, 2026

A dynamic hybrid attention-based autoencoder model with adaptive contextual attention for grammatical error correction.
Int. J. Mach. Learn. Cybern., January, 2026

2025
An adaptive binary particle swarm optimization algorithm with filtration and local search for feature selection in text classification.
Memetic Comput., December, 2025

An optimal feature selection method for text classification through redundancy and synergy analysis.
Multim. Tools Appl., May, 2025

Hybrid Accurate Localization Approach for Dense and Highly Mobile Vehicular Networks.
Int. J. Commun. Syst., March, 2025

2024
A hybrid feature selection method for text classification using a feature-correlation-based genetic algorithm.
Soft Comput., December, 2024

Semantic similarity-aware feature selection and redundancy removal for text classification using joint mutual information.
Knowl. Inf. Syst., October, 2024

Feature redundancy removal for text classification using correlated feature subsets.
Comput. Intell., February, 2024

A non-redundant feature selection method for text categorization based on term co-occurrence frequency and mutual information.
Multim. Tools Appl., 2024

2019
Fuzzy clustering-based semi-supervised approach for outlier detection in big text data.
Prog. Artif. Intell., 2019

Implicit feature identification for opinion mining.
Int. J. Bus. Inf. Syst., 2019

2018
Mining hidden opinions from objective sentences.
Int. J. Data Min. Model. Manag., 2018

2016
Mining explicit and implicit opinions from reviews.
Int. J. Data Min. Model. Manag., 2016


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