Djamel Amar Bensaber

Ecole supérieure en Informatique sidi bel abbes

Particle swarm optimization (PSO) has been successfully applied to feature selection (FS) due to its efficiency and ease of implementation. Like most evolutionary algorithms, they still suffer from a high computational burden and poor generalization ability. Multifactorial optimization (MFO), as an effective evolutionary multitasking paradigm, has...

Recent developments in remote sensing technology have allowed us to observe the Earth with very high-resolution (VHR) images. VHR imagery scene classification is a challenging problem in the field of remote sensing. Vision transformer (ViT) models have achieved breakthrough results in image recognition tasks. However, transformer–encoder layers enc...

The meaning negotiation process has become a confusing term in the pragmatic web. It does not depend only on convenience to agree, but requires an excellent choice of terms used in the negotiated domain. The presented paper proposes a meaning negotiation model using ontologies merging into several domains and contextual situations. The idea is to d...

Classification algorithms face runtime complexity due to high data dimension, especially in the context of big data. Feature selection (FS) is a technique for reducing dimensions and improving learning performance. In this paper, the authors proposed a hybrid FS algorithm for classification in the context of big data. Firstly, only the most relevan...

Cloud Computing is a dynamic and elastic environment, these characteristics make them vulnerable to faults, such as VMs and host failures or software bugs, which affects the quality of service provided by Cloud Computing platforms. The adoption of a fault tolerance mechanism is essential to ensure the smooth functioning of these platforms, as well...

This article describes how the Linked Open Data Cloud project allows data providers to publish structured data on the web according to the Linked Data principles. In this context, several link discovery frameworks have been developed for connecting entities contained in knowledge bases. In order to achieve a high effectiveness for the link discover...

Purpose This paper aims to solve the problems of big data analytics for prediction including volume, veracity and velocity by improving the prediction result to an acceptable level and in the shortest possible time. Design/methodology/approach This paper is divided into two parts. The first one is to improve the result of the prediction. In this...

Semantic mashup applications allow automating the process of services and data integration to create a composite application with a new user interface. Nevertheless, existing mashup applications need to improve the matching methods for discovering semantic services. Moreover, they have to create or modify workflows in mashup applications without th...

In traditional search engines, different users with diverse intentions submitting the same keywords would receive the same results. Semantic Search will provide relevant results according to the user profile. In this paper, user's activities and preferences in social networks are used to build a user profile. We propose a novel approach to extract,...