Ahmed Oussous

Ahmed Oussous
Université Hassan II de Casablanca · Department of Computer Sciences

Professor

About

15
Publications
28,466
Reads
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838
Citations
Citations since 2016
13 Research Items
838 Citations
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Introduction
Ahmed Oussous currently works at the Department of Computer Sciences, Université Hassan 2. Ahmed does research in Algorithms,Big Data , Data Mining and Distributed Computing. Their current project is 'Big Data'.

Publications

Publications (15)
Article
In the era of big data, recommender systems (RSs) have become growing essential tools. They represent important machine learning solutions that mainly contribute to keeping users engaged with personalized content in e-platforms. Several RSs have been proposed in the literature, and most of them have focused on English content. However, for content...
Article
Full-text available
The exponential growth of data generated from the Moroccan court makes it difficult to search for valuable knowledge within multiple and huge data sets. Traditional searching methods are not adapted to Big Data context. Indeed, handling the search of specific information on Big Data requires advanced methods and a powerful search systems. To contri...
Chapter
Sentiment analysis (SA) or opinion mining constitutes an important scientific field that uses advanced methods to mine population’s views and determine their feelings. In fact, SA is exploited by many fields. In politics, SA can mine the citizens’ opinions posted online and use this data as a means to predict the results of an ongoing election. Mor...
Article
Full-text available
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 the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglec...
Article
Full-text available
In e-commerce websites and related micro-blogs, users supply online reviews expressing their preferences regarding various items. Such reviews are typically in the textual comments form, and account for a valuable information source about user interests. Recently, several works have used review texts and their related rich information like review w...
Article
Full-text available
Detecting outliers in real-time is increasingly important for many real-world applications such as detecting abnormal heart activity, intrusions to systems, spams or abnormal credit card transactions. However, detecting outliers in data streams rises many challenges such as high-dimensionality, dynamic data distribution and unpredictable relationsh...
Article
Full-text available
Sentiment analysis (SA), also known as opinion mining, is a growing important research area. Generally, it helps to automatically determine if a text expresses a positive, negative or neutral sentiment. It enables to mine the huge increasing resources of shared opinions such as social networks, review sites and blogs. In fact, SA is used by many fi...
Conference Paper
Nowadays, with the rapid growth and spread of web platforms such as social networks, online review websites and blogs, people can openly express and share their opinions. They can rate products or comment various subjects. Thus, a new field called web based Sentiment Analysis (SA) or Opinion Mining has emerged. In general, SA is the process of clas...
Chapter
With the proliferation of the internet and the social media, increasing huge contents are generated each day across the world. Such huge data mines attract the attention of many entities. Indeed, by analyzing sentiments expressed in such content, government, businesses and particulars can extract valuable knowledge in order to enhance their strateg...
Article
Full-text available
Developing Big Data applications has become increasingly important in the last few years. In fact, several organizations from different sectors depend increasingly on knowledge extracted from huge volumes of data. However, in Big Data context, traditional data techniques and platforms are less efficient. They show a slow responsiveness and lack of...
Article
Abstract NoSQL solutions have been created to respond to many issues encountered when dealing with some specific applications like those of Big Data (e.g., storage of very large data sets, the need of cheaper storage or the need of less management overhead in the Cloud). In fact, the traditional RDMS ensures data integrity and transaction consiste...
Conference Paper
Full-text available
NoSQL solutions have been created to respond to many issues encountered when dealing with some specific applications like those of Big Data (e.g., storage of very large data sets, the need of cheaper storage or the need of less management overhead in the Cloud). In fact, the traditional RDMS ensures data integrity and transaction consistency. But,...
Conference Paper
De nos jours, la multiplication des systèmes informatiques distribués, l’évolution de l’Internet des Objets (Internet Of Things) et l’utilisation massive des dispositifs électroniques (smartphones, capteurs, etc.) permettent d’accéder facilement à de grands volumes de données numériques. Ces données sont générées par les réseaux sociaux, sites d’e-...

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Projects (3)
Project
https://sites.google.com/view/iwsmai/ Artificial intelligence (AI) is mainly data-driven. It uses statistical methods through human-machine relationships during generation of data, production of algorithm, and prediction of results. The International Workshop on Statistical Methods and Artificial Intelligence will be an annual meeting of researchers in artificial intelligence, statistical methods, machine learning, and related areas. This workshop will include (but will not be limited to) the following topics: 1. Artificial Intelligence 2. Statistical methods 3. Data Analysis and Data mining 4. Computational Statistic 5. Supervised and unsupervised learning 6. Statistical methodology 7. Bioinformatics 8. Medical statistics 9. Deep Learning 10. Data Collection and Applications 11. Data Science and Blockchain Technology 12. Data Science and Artificial Intelligence 13. Data Science and Blockchain Technology 14. Mathematical Statistics 15. Sampling Techniques and Applications 16. Statistical Software (R, SAS, Python) 17. Neural network 18. Epidemic model