Search Results - "Lahcen, Ayoub Ait"

Recommender Systems Based on Collaborative Filtering Using Review Texts—A Survey by Srifi, Mehdi, Oussous, Ahmed, Ait Lahcen, Ayoub, Mouline, Salma

“…In e-commerce websites and related micro-blogs, users supply online reviews expressing their preferences regarding various items. Such reviews are typically in…”
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Big data analytics in telecommunications: Governance, architecture and use cases by Kastouni, Mohamed Zouheir, Ait Lahcen, Ayoub

“…With the upsurge of data traffic due to the change in customer behavior towards the use of telecommunications services, fostered by the current global health…”
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A distributed group recommendation system based on extreme gradient boosting and big data technologies by Ait Hammou, Badr, Ait Lahcen, Ayoub, Mouline, Salma

“…Personalized recommendation systems have emerged as useful tools for recommending the appropriate items to individual users. However, in such situations, some…”
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Evaluation of recent advances in recommender systems on Arabic content by Srifi, Mehdi, Oussous, Ahmed, Ait Lahcen, Ayoub, Mouline, Salma

“…Various recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from…”
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Improving outliers detection in data streams using LiCS and voting by Benjelloun, Fatima-Zahra, Oussous, Ahmed, Bennani, Amine, Belfkih, Samir, Ait Lahcen, Ayoub

“…Detecting outliers in real-time is increasingly important for many real-world applications such as detecting abnormal heart activity, intrusions to systems,…”
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Towards a real-time processing framework based on improved distributed recurrent neural network variants with fastText for social big data analytics by Ait Hammou, Badr, Ait Lahcen, Ayoub, Mouline, Salma

“…•We present an effective distributed intelligent system for real-time social big data analytics, which is dedicated to ingest, store, process, index, and…”
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ASA: A framework for Arabic sentiment analysis by Oussous, Ahmed, Benjelloun, Fatima-Zahra, Lahcen, Ayoub Ait, Belfkih, Samir

“…Sentiment analysis (SA), also known as opinion mining, is a growing important research area. Generally, it helps to automatically determine if a text expresses…”
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An effective distributed predictive model with Matrix factorization and random forest for Big Data recommendation systems by Ait Hammou, Badr, Ait Lahcen, Ayoub, Mouline, Salma

“…•A distributed predictive model is proposed for Big Data recommendations.•A data partitioning strategy is adopted to speed up Big Data processing.•A novel…”
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XGBoost To Enhance Learner Performance Prediction by Hakkal, Soukaina, Lahcen, Ayoub Ait

“…The huge amount of data generated by an Intelligent Tutoring System becomes useful when analyzed in an appropriate way to provide significant insights about…”
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APRA: An approximate parallel recommendation algorithm for Big Data by Ait Hammou, Badr, Ait Lahcen, Ayoub, Mouline, Salma

“…Finding relevant and interesting items according to the preferences of each user has become an important challenge in the era of Big Data. Recommender systems…”
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FRAIPA version 2: A fast recommendation approach based on self-adaptation and multi-thresholding by Ait Hammou, Badr, Ait Lahcen, Ayoub, Mouline, Salma

“…•A fast recommendation approach is proposed.•The approach is based on self-adaptation and multi-thresholding.•An automatic convergence procedure is proposed to…”
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FRAIPA: A fast recommendation approach with improved prediction accuracy by Ait Hammou, Badr, Ait Lahcen, Ayoub

“…•A novel recommendation approach called FRAIPA is proposed.•The quality of predictions is improved.•The computation time is shortened.•The experimentations…”
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Forwarding strategies in vehicular named data networks: A survey by Ahed, Kaoutar, Benamar, Maria, Lahcen, Ayoub Ait, Ouazzani, Rajae El

“…The traditional Internet architecture provides applications with a stable end-to-end connection between a requester and a source node holding the information…”
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Big Data Technologies: A Survey by Oussous, Ahmed, Benjelloun, Fatima Zahra, Ait Lahcen, Ayoub, Belfkih, Samir

“…Developing Big Data applications has become increasingly important in the last few years. In fact, several organizations from different sectors depend…”
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An Evaluation of Open Source Adaptive Learning Solutions by Oussous, Ahmed, Menyani, Ismail, Srifi, Mehdi, Lahcen, Ayoub Ait, Kheraz, Smail, Benjelloun, Fatima-Zahra

“…The education sector has never been so shaken up as much as this past year. COVID-19 has imposed new rules. Several countries were forced to switch overnight…”
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A Lightweight Middleware for Developing P2P Applications with Component and Service-Based Principles by Lahcen, A. A., Parigot, D.

“…Developing Peer-to-Peer (P2P) applications became increasingly important in software development. Nowadays, a large number of organizations from many different…”
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Design of a Domain Specific Language for modelling processes in landscapes by Degenne, P., Lo Seen, D., Parigot, D., Forax, R., Tran, A., Ait Lahcen, A., Curé, O., Jeansoulin, R.

“…The modelling of processes that occur in landscapes is often confronted to issues related to the representation of space and the difficulty of properly…”
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Evaluating Recommender Systems when Applied to Arabic Content by Srifi, Mehdi, Oussous, Ahmed, Lahcen, Ayoub Ait, Mouline, Salma

“…In the era of big data, many works have proposed recommender systems (RSs) to handle the information overload issue. Among them, very few studies have focused…”
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Collaborative Recommender Systems Based on User-Generated Reviews: A Concise Survey by Srifi, Mehdi, Hammou, Badr Ait, Mouline, Salma, Lahcen, Ayoub Ait

“…Recommender systems are powerful tools that help users to deal with information overload problem. Collaborative Filtering (CF) approach has been widely used to…”
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Detection and elimination of class noise in large datasets using partitioning filter technique by Zerhari, Btissam, Lahcen, Ayoub Ait, Mouline, Salma

“…Class noise elimination in large databases is a real issue in data mining processing. In fact, class noise may sometimes lead to distortion or inaccuracy. So…”
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