@conference {Ouardi2021790,
	title = {Hybrid Prototypical Networks Augmented by a Non-linear Classifier},
	booktitle = {International Conference on Enterprise Information Systems, ICEIS - Proceedings},
	volume = {1},
	year = {2021},
	note = {cited By 0},
	pages = {790-794},
	abstract = {Text classification is one of the most prolific domains in machine learning. Present in a raw format all around us in our daily life Starting from human to human communication mainly by the social networks apps, arriving at the human-machine interaction especially with chatbots, text is a rich source of information. However, despite the remarkable performances that deep learning achieves in this field, the cost in therm of the amount of data needed to train this model still considerably high, adding to that the need of retraining this model to learn every new task. Nevertheless, a new sub-field of machine learning has emerged, named meta-learning it targets the overcoming of those limitations, widely used for image-related tasks, it can also bring solutions to tasks associated with text. Starting from this perspective we proposed a hybrid architecture based on well-known prototypical networks consisting of adapting this model to text classification and augmenting it with a non-linear classifier. Copyright {\textcopyright} 2021 by SCITEPRESS {\textendash} Science and Technology Publications, Lda. All rights reserved.},
	keywords = {Chatbots, Classification (of information), Daily lives, Deep learning, Few-shot learning, Human communications, Human machine interaction, Learning systems, Machine-learning, Metalearning, Nonlinear classifiers, Sources of informations, Text classification, Text processing},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137962135\&partnerID=40\&md5=8d0e3e181cd871cde23a9553ea783fb2},
	author = {Ouardi, A.E. and Rhanoui, M. and Benlarabi, A. and Asri, B.E.}
}
@article {Benlarabi2015550,
	title = {Analyzing trends in software product lines evolution using a cladistics based approach},
	journal = {Information (Switzerland)},
	volume = {6},
	number = {3},
	year = {2015},
	note = {cited By 1},
	pages = {550-563},
	abstract = {Abstract: A software product line is a complex system the aim of which is to provide a platform dedicated to large reuse. It necessitates a great investment. Thus, its ability to cope with customers{\textquoteright} ever-changing requirements is among its key success factors. Great effort has been made to deal with the software product line evolution. In our previous works, we carried out a classification of these works to provide an overview of the used techniques. We also identified the following key challenges of software product lines evolution: the ability to predict future changes, the ability to define the impact of a change easily and the improvement in understanding the change. We have already tackled the second and the third challenges. The objective of this paper is to deal with the first challenge. We use the cladistics classification which was used in biology to understand the evolution of organisms sharing the same ancestor and their process of descent at the aim of predicting their future changes. By analogy, we consider a population of applications for media management on mobile devices derived from the same platform and we use cladistics to construct their evolutionary tree. We conducted an analysis to show how to identify the evolution trends of the case study products and to predict future changes. {\textcopyright} 2015 by the authors.},
	doi = {10.3390/info6030550},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943561816\&doi=10.3390\%2finfo6030550\&partnerID=40\&md5=892c17009c76fbae807d486836450566},
	author = {Benlarabi, A. and Khtira, A. and El Asri, B.}
}
@article {Khtira2015592,
	title = {Duplication detection when evolving feature models of software product lines},
	journal = {Information (Switzerland)},
	volume = {6},
	number = {4},
	year = {2015},
	note = {cited By 1},
	pages = {592-612},
	abstract = {After the derivation of specific applications from a software product line, the applications keep evolving with respect to new customer{\textquoteright}s requirements. In general, evolutions in most industrial projects are expressed using natural language, because it is the easiest and the most flexible way for customers to express their needs. However, the use of this means of communication has shown its limits in detecting defects, such as inconsistency and duplication, when evolving the existing models of the software product line. The aim of this paper is to transform the natural language specifications of new evolutions into a more formal representation using natural language processing. Then, an algorithm is proposed to automatically detect duplication between these specifications and the existing product line feature models. In order to instantiate the proposed solution, a tool is developed to automatize the two operations. {\textcopyright} 2015 by the authors.},
	doi = {10.3390/info6040592},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952314845\&doi=10.3390\%2finfo6040592\&partnerID=40\&md5=0661de379421d5877cc91927d0c41731},
	author = {Khtira, A. and Benlarabi, A. and El Asri, B.}
}
@conference {Benlarabi2014140,
	title = {A co-evolution model for software product lines: An approach based on evolutionary trees},
	booktitle = {2014 2nd World Conference on Complex Systems, WCCS 2014},
	year = {2014},
	note = {cited By 3},
	pages = {140-145},
	abstract = {Software product line engineering allows for the development of common reference assets that can be reused in the development of a set of products of a particular market, the purpose of such large scale reuse is the improvement of time to market and the reduction of costs. This goal can only be achieved if the software product line assets are continuously evolved to cope with changes of user requirements. In this paper we present a co-evolution model for checking the integrity of the software product line during its evolution. The model is established using cladistics and trees reconciliation that are used in biology to analyze the co-evolution between organisms. This model shows the divergent co-evolution which represents a difference between the evolutionary trees of the software product line and a derived product. The model helps to find out changes of products that were not propagated to the reference assets and to anticipate the future development to be done on these reference assets to cope with products evolution. By its application we protect software product lines from the aging phenomenon. {\textcopyright} 2014 IEEE.},
	doi = {10.1109/ICoCS.2014.7060991},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929164049\&doi=10.1109\%2fICoCS.2014.7060991\&partnerID=40\&md5=8647fe4ff84bea2b02dd50b90e0d9bb9},
	author = {Benlarabi, A. and El Asri, B. and Khtira, A.}
}
@conference {Khtira2014152,
	title = {Towards a requirement-based approach to support early decisions in software product line engineering},
	booktitle = {2014 2nd World Conference on Complex Systems, WCCS 2014},
	year = {2014},
	note = {cited By 0},
	pages = {152-157},
	abstract = {During the creation of a software product, the stakeholders have to take a lot of decisions. These decisions are related to the product scope, requirements priority, architecture assumptions, technological issues, etc. In the domain of Software Product Lines, many studies have dealt with decisions taken during the lifetime of the product, but a little attention has been given to the pre-project decisions. The aim of this paper is to propose a requirement-based framework that capitalizes on the specific products already derived from the product line, in order to support the benchmarking of the possible solutions that respond to a customer{\textquoteright}s needs, and to help the stakeholders of a product take decisions concerning the scope of the product and the requirements to implement. {\textcopyright} 2014 IEEE.},
	doi = {10.1109/ICoCS.2014.7060993},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988286512\&doi=10.1109\%2fICoCS.2014.7060993\&partnerID=40\&md5=d227ca52b5793a11500365eb9248052c},
	author = {Khtira, A. and Benlarabi, A. and El Asri, B.}
}
