Juliana Alves Pereira
Pawel Matuszyk
ABSTRACT
Today’s competitive marketplace requires the industry to understand unique and particular needs of their customers. Product line practices enable companies to create individual products for every customer by providing an interdependent set of features. Users configure personalized products by consecutively selecting desired features based on their individual needs. However, as most features are interdependent, users must understand the impact of their gradual selections in order to make valid decisions. Thus, especially when dealing with large feature models, specialized assistance is needed to guide the users in configuring their product. Recently, recommender systems have proved to be an appropriate mean to assist users in finding information and making decisions. In this paper, we propose an advanced feature recommender system that provides personalized recommendations to users. In detail, we offer four main contributions: (i) We provide a recommender system that suggests relevant features to ease the decision-making process. (ii) Based on this system, we provide visual support to users that guides them through the decision-making process and allows them to focus on valid and relevant parts of the configuration space. (iii) We provide an interactive open-source configurator tool encompassing all those features. (iv) In order to demonstrate the performance of our approach, we compare three different recommender algorithms in two real case studies derived from business experience.
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Index Terms
- A feature-based personalized recommender system for product-line configuration
Recommendations
A Context-Aware Recommender System for Extended Software Product Line Configurations
VAMOS '18: Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive SystemsMass customization of standardized products has become a trend to succeed in today's market environment. Software Product Lines (SPLs) address this trend by describing a family of software products that share a common set of features. However, choosing ...
A feature-based personalized recommender system for product-line configuration
GPCE '16Today’s competitive marketplace requires the industry to understand unique and particular needs of their customers. Product line practices enable companies to create individual products for every customer by providing an interdependent set of features. ...
Personalized recommender systems for product-line configuration processes
Highlights- We adapt six state-of-the-art recommendation algorithms to the context of product-line configuration.
AbstractProduct lines are designed to support the reuse of features across multiple products. Features are product functional requirements that are important to stakeholders. In this context, feature models are used to establish a reuse ...
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