Mitigation of Popularity Bias in Recommendation Systems

In response to the quantity of information available on the Internet, many online service providers are attempting to customize their services and make content access more simple via recommender systems (RSs) to support users in discovering the products they are most likely interested in. However, these recommendation systems are prone to popularity bias, which is a tendency to promote popular items even if they do not satisfy a user’s preferences and then provide customers with recommendations of poor quality. Such a bias has a negative influence on both users and item providers. It is then essential to mitigate such bias in order to guarantee that less popular but pertinent items show up on the user’s recommendation list. In this work, we conduct an empirical analysis of different mitigation techniques for popularity bias to provide an overview of the present state of the art of popularity bias and raise the fairness issue in RSs

Arabic Opinion Mining Using a Hybrid Recommender System Approach

Recommender systems nowadays are playing an important role in the delivery of services and information to users. Sentiment analysis (also known as opinion mining) is the process of determining the attitude of textual opinions, whether they are positive, negative or neutral. Data sparsity is representing a big issue for recommender systems because of the insufficiency of user rating or absence of data about users or items. This research proposed a hybrid approach combining sentiment analysis and recommender systems to tackle the problem of data sparsity problems by predicting the rating of products from users reviews using text mining and NLP techniques. This research focuses especially on Arabic reviews, where the model is evaluated using Opinion Corpus for Arabic (OCA) dataset. Our system was efficient, and it showed a good accuracy of nearly 85 percent in predicting rating from review

MPPT Fuzzy Logic Control of a Variable Speed Wind Turbine

This work is focused on the control of a wind turbine system based on (PMSG). In order to enhance the efficiency of the wind turbine system, the maximum power point tracking (MPPT) control is applied to exploit the maximum power from the wind. The Fuzzy Logic controller (FLC) has been proposed and developed for the speed control. The simulation results show good performances of this control

Codeposition electrolytique de zinc et de cadmium sur acier doux : resistance a la corrosion

CNRS TD Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

Tax havens and losses of the global tax system With reference to the case of Algeria: الجنات الضريبية وخسائرالنظام الضريبي العالمي مع الإشارة لحالة الجزائر

ارتبط الظهور الأول للجنات الضريبية بجذب الاستثمارات الأجنبية، إلا أنها أضحت من أهم آليات التهرب الضريبي الدولي في العصر الحالي، وذلك من خلال تمكين الممارسات السلبية للأفراد والشركات، مما يكلف النظام الضريبي العالمي خسارة 427 مليار دولار سنويا، 46,86% من إجمالي الخسائر مسؤولية جزر كايمان، بريطانيا، هولندا، لكسمبورغ، الو.م.أ. وتخسر الجزائر سنويا حوالي 429 مليون دولار(ما يعادل1,94% من إيراداتها الضريبية). لذلك فقد جاءت هذه الدراسة لتسلط الضوء على هذه الظاهرة التي شهدت اتساعا كبيرا في السنوات الأخيرة، والحث على تسطير استراتيجيات دولية للحد من اتساعها. The first appearance of tax havens is related to attracting foreign investment, But it has become one of the most important mechanisms of international tax evasion in the current era, costing the global tax system a loss of 427 billion annually, And 46,86% of the total losses are the responsibility of the Cayman Islands, Britain, the Netherlands, Luxemburg, USA. Algeria loses about $429 million a year, so this study came to highlight this phenomenon, urging the need to develop strategies to reduce its breadth