Tracks > Artificial Intelligence, NLP, Clouding and Metaheuristic

CALL FOR PAPERS 

Special Session 

Artificial Intelligence, NLP, Clouding and Metaheuristic 

Session chair

Rachida FISSOUNE, Aimad EL MOURABIT, Ladjel BELLATERECHE

IDS Team-Lab Tangier-Morocco, Lias Poitiers France 

The 9th INTIS 2020 Conference (Innovation and New Trends in Information Systems) also includes a special session entitled « Artificial Intelligence & Machine Learning «IDS Laboratory, Lias Lab Poitiers; You are invited to participate in this special session, which focuses on issues related to the Artificial Intelligence, NLP, Clouding and Metaheuristic.

Artificial Intelligence (AI) is an area of computer science dedicated to solving cognitive problems typically associated with human intelligence, such as learning, problem solving, and pattern recognition. Artificial intelligence, often abbreviated as « AI », can evoke robotics or a futuristic world, but this discipline goes beyond science fiction automata to apply to today’s actual advanced computing. Similarly, advances in network computing have allowed connectionists to deepen a subdomain called « machine learning ». Machine Learning (AM) and Deep Learning (AP) are both computer science-domains derived from Artificial Intelligence. Machine learning is basically a series of algorithms that can learn and make predictions from stored data, optimize a given utility function in an uncertain situation, extract hidden structures in data, and classify data into concise descriptions. Deep learning is a branch of machine learning that consists of superimposing algorithms to better understand the data. It relies on these layers of nonlinear algorithms to create distributed representations that interact based on a series of factors.

However, AI’s cognitive and machine learning capabilities are based on huge volumes of data, which in turn become scalable and instantly accessible in the cloud. The primary goal of this track  is to promote research and developmental activities in Meta-heuristic and Optimisation, Natural Language Processing and social networking.

Natural Language Processing (NLP) is a subset of artificial intelligence that focuses on system development that allows computers to communicate with people using everyday language. Natural language generation system converts information from computer database into readable human language and vice versa.

A metaheuristic is a set of algorithmic concepts that can be used to define heuristic methods applicable to a wide set of different problems. A metaheuristic can be seen as a general purpose heuristic method toward promising regions of the search space containing high-quality solutions. A metaheuristic is a general algorithmic framework which can be applied to different optimization problems with relatively few modifications to make them adapted to a specific problem.

The first objective is intended to present works ranking from Artificial Intelligence, Machine learning, Deep learning, NLP and clouding.  The second objective is to target researchers interested in all aspects of the application of intelligent techniques in order to present, discuss and share original research works and practical experiences, and provide the latest and most innovative contributions.

Papers and contributions are encouraged for any work relating to Artificial Intelligence. Topics of interest may include (but are in no way limited to):

• Case-Based Reasoning and Learning
• Classification and Model Estimation
• Statistical and Evolutionary Learning
• Statistical Learning and Neural Net Based Learning
• Text, Video and, Image Mining
• Cloud Computing and Business Intelligence
• Data Analytics in Cloud
• Deep Learning and its Applications
• Fast Learning Methods
• Internet of Things
• Machine Learning in AI
• Secrurity and Privacy Preserving using Data Mining
• Analysis of speech & speech recognition system and language identification
• Computational Social Web
• Text categorization, text classification and clustering
• Evolutionary Computation and Genetic Programming
• Information extraction & Information Retrieval
• Knowledge management systems
• Lexical semantics and knowledge representation
• Meta-heuristics
• Swarm Intelligence & Multi-Agent Systems
• Optimization , Preference Reasoning and Planning and Scheduling
• Sentiment analysis and opinion mining and Social Networks Applications

TPC Member :

•  Otmane AIT MOHAMED, Concordia University, Canada
•  Muhammad Arif, School of Computer Science and Educational Software, Guangzhou University, Guangzhou, China
•  Hassan BADIR – Université of Tanger, Maroc
• Valentina Emilia BALAS- « Aurel Vlaicu » University of Arad, Roumanie
• Omar BOUSSAID – ERIC Laboratory, Lyon, France
• Gazi Erkan Bostanci, Ankara University, Turkey
• Maria Cecilia G. Cantos, Manuel S. Enverga University Foundation, Philippines
• Adriana Coroiu, Babeș-Bolyai University, Cluj-Napoca, Romania
• Smain Femmam, UHA University, France
• José Eduardo Moreira Fernandes, Polytechnic Institute of Bragança, Portugal
• Rachida FISSOUNE – ENSAT, Maroc
• Alexander Gelbukh Instituto Politécnico Nacional, Mexico
• Damien Hanyurwimfura, University of Rwanda
• Alessio Ishizaka, university of Portsmouth, United Kingdom
• Abdelouahid IMLAHI, Abdelmalek Essaadi University, FST-Tangier, Morocco
• Gabor Kiss, Obuda University, Budapest, Hungary
• Siham KOUIDRI, GeCoDe Lab, University of Saïda, Algeria

•  Raghvendra Kumar, LNCT Group of College, Jabalpur, India
•  Sonia LADJIMI, University of sfax, Tunisia
•  Ramona Lile, « Aurel Vlaicu » University of Arad, Romania
•  Tsung-Chih Lin, Feng Chia University, Taichung, Taiwan
•  Ahmed Chaouki LOKBANI, GeCoDe Lab, University of Saïda, Algeria
•  Edwin Lughofer, Johannes Kepler University Linz, Austria
•  Antoanela Naaji, “Vasile Goldis” Western University of Arad, Romania
•  Cenap Ozel, Department of Mathematics, King Abdulaziz University, Kingdom of Saudi Arabia
•  Tiago Pedrosa, Polytechnic Institute of Bragança, Portugal
•  Emil Pricop, Oil & Gas University of Ploiești, Romania
•  Dana Rad, Aurel Vlaicu University of Arad, Romania.
•  Hamid Rastegari, Islamic Azad University, Iran
•  Marjan Kuchaki Rafsanjani, Shahid Bahonar University of Kerman, Kerman, Iran
•  D. Vijay Rao, Institute of System Studies and Analysis, Delhi, India
•  Fatima Ruksar, vice Principal KBNCE Kalaburagi, India
•  Roselina Sallehuddin, Universiti teknologi malaysia, Malaysia
•  Mohamed Saraee, University of Salford-Manchester, UK
•  Ranbir Singh, Lovely Professional University, Jalandar, India
•  Vijender Kr. Solanki, CMR Institute of Technology, Hyderabad, India,
•  Sebastián Ventura Soto, University of Cordoba, Spain
•  I-Hsien Ting, National University of Kaohsiung, Taiwan
•  Vikash Yadav, ABES Engineering College, Ghaziabad, India
•  Mebarka YAHLALI, GeCoDe Lab, University of Saïda, Algeria

Paper submission:

Authors are invited to submit papers of 6-8 pages including results, figures and references via the conference website: (https://easychair.org/conferences/?conf=intis2020).

Important Dates: 

• Paper Submission (6 - 8 pages):  October 10, 2020  
• Author Notification:  November 10, 2020 
• Final Version of the Papers:  Novemver 30, 2020
• Registration Deadline:  December 10, 2020
• Conference Dates: 18 - 19 December 2020

General Information :

•  Rachida FISSOUNE, IDS Team-Lab, Tangier-Morocco  
•  Imad EL MOURABIT, IDS Team-Lab, Tangier-Morocco  
•  Ladjel BELLATRECH, LIAS Lab, Poitiers-France