Toward a Deep Contextual Product Recommendation for SO-DSPL Framework

Najla Maalaoui, Raoudha Beltaifa, Lamia Jilani

2023

Abstract

Today’s demand for customized service-based systems requires that industry understands the context and the particular needs of their customers. Service Oriented Dynamic Software Product Line practices enable companies to create individual products for every customer by providing an interdependent set of features presenting web services that are automatically activated and deactivated depending on the running situation. Such product lines are designed to support their self-adaptation to new contexts and requirements. Users configure personalized products by selecting desired features based on their needs. However, with large feature models, users must understand the functionalities of features and the impact of their gradual selections and their current context in order to make appropriate decisions. Thus, users need to be guided in configuring their product. To tackle this challenge, users can express their product requirements by textual language and a recommended product will be generated with respect to the described requirements. In this paper, we propose a deep neural network based recommendation approach that provides personalized recommendations to users which ease the configuration process. In detail, our proposed recommender system is based on a deep neural network that predicts to the user relevant features of the recommended product with the consideration of their requirements, contextual data and previous recommended products. In order to demonstrate the performance of our approach, we compared six different recommendation algorithms in a smart home case study.

Paper Citation

in Harvard Style

Maalaoui N., Beltaifa R. and Jilani L. (2023). Toward a Deep Contextual Product Recommendation for SO-DSPL Framework. In Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-647-7, SciTePress, pages 138-148. DOI: 10.5220/0011855800003464

in Bibtex Style

@conference{enase23,
author={Najla Maalaoui and Raoudha Beltaifa and Lamia Jilani},
title={Toward a Deep Contextual Product Recommendation for SO-DSPL Framework},
booktitle={Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2023},
pages={138-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011855800003464},
isbn={978-989-758-647-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Toward a Deep Contextual Product Recommendation for SO-DSPL Framework
SN - 978-989-758-647-7
AU - Maalaoui N.
AU - Beltaifa R.
AU - Jilani L.
PY - 2023
SP - 138
EP - 148
DO - 10.5220/0011855800003464
PB - SciTePress