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F Meziane

Contact
Biography
My Most Viewed
My Latest

[+][-]

Contact

Name:

F Meziane

Email:

F.Meziane@salford.ac.uk

Department:

School of Science, Engineering & Environment

Organisation:

University of Salford

Address:

School of Computing, Science and Engineering Newton Building University of Salford M5 4WT

Country:

Homepage:

http://www.salford.ac.uk/computing-science-engineering/cse-academics/farid-meziane

profile_image:

Biography

Expertise:

Knowledge Engineering, Data intensive computing, software engineering, Natural Language Processing

Qualifications:

PhD FBCS CITP

My Most Viewed

#	Item title
1.	AI in software engineering : current developments and future prospects	1594	6540
2.	Challenges to describe QoS requirements for web services quality prediction to support web services interoperability in electronic commerce	993	1226
3.	Artificial intelligence applications for improved software engineering development : new prospects	977
4.	Intelligent systems in manufacturing: current developments and future prospects	737	9266
5.	Obtaining E-R diagrams semi-automatically from natural language specifications	662	731
6.	Evaluating e-commerce trust using fuzzy logic [article]	641	1235
7.	Generating natural language specifications from UML class diagrams	632	2617
8.	A method for maintaining document consistency based on similarity contents	594	346
9.	Current state on internet growth and usage in Saudi Arabia and its ability to support e-commerce development	572	481
10.	Evaluating e-commerce trust using fuzzy logic	567

My Latest

Peng, J, Jiang, Y, Tang, S and Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 2021, 'Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography' , IEEE Transactions on Dependable and Secure Computing, 18 (4) , pp. 1962-1973.
Kayhani, AK, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 and Chiky, R 2020, Movies emotional analysis using textual contents , in: 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, 24-26 June 2020, Saarbrücken, Germany.
Silberztein, M, Métais, E, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914, Kornyshova, E and Atigui, F 2020, 'Preface (Volume 127)' , Data & Knowledge Engineering, 127 , p. 101775.
Hadj Ameur, MS, Guessoum, A and Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 2019, 'Improving Arabic neural machine translation via n-best list re-ranking' , Machine Translation, 33 , pp. 279-314.
Boussouar, A ORCID: https://orcid.org/0000-0002-2674-1734, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 and Walton, LA ORCID: https://orcid.org/0000-0002-8651-7443 2019, Plantar fascia ultrasound images characterization and classification using support vector machine , in: The 5th International Conference on Advanced Intelligent Systems and Applications, 26-28 October 2019, Cairo, Egypt.
Zulkarnain, NZ ORCID: https://orcid.org/0000-0003-0001-7948 and Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 2019, 'A methodology for ontology reuse : the case of the abdominal ultrasound ontology' , International Journal of Intelligent Information Technologies, 15 (4) , pp. 1-21.
Qasim, A, Aspin, R ORCID: https://orcid.org/0000-0002-2202-1326 and Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 2019, Integration of digital watermarking technique into medical imaging systems , in: 10th International Conference Dependable Systems, Services and Technologies (DESSERT’2019), 5-7 June 2019, Leeds, UK.
Hadj Ameur, MS, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 and Guessoum, A 2019, ANETAC: Arabic named entity transliteration and classification dataset , Documentation, arXiv.
Hadj Ameur, MS, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 and Guessoum, A 2019, ANETAC: Arabic named entity transliteration and classification dataset [Dataset].
Qasim, A, Aspin, R ORCID: https://orcid.org/0000-0002-2202-1326, Meziane, F ORCID: https://orcid.org/0000-0001-9811-6914 and Hogg, P ORCID: https://orcid.org/0000-0002-6506-0827 2019, 'ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images' , Multimedia Tools and Applications, 78 (12) , pp. 16433-16463.