An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration

Alexander Felfernig; Viet-Man Le; Andrei Popescu; Mathias Uta; Trang Tran; Müslüm Atas

doi:10.1145/3442391.3442408

An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration

Alexander Felfernig, Viet-Man Le, Andrei Popescu, Mathias Uta, Trang Tran, Müslüm Atas

Institute of Software Technology (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Recommender systems support decisions in various domains ranging from simple items such as books and movies to more complex items such as financial services, telecommunication equipment, and software systems. In this context, recommendations are determined, for example, on the basis of analyzing the preferences of similar users. In contrast to simple items which can be enumerated in an item catalog, complex items have to be represented on the basis of variability models (e.g., feature models) since a complete enumeration of all possible configurations is infeasible and would trigger significant performance issues. In this paper, we give an overview of a potential new line of research which is related to the application of recommender systems and machine learning techniques in feature modeling and configuration. In this context, we give examples of the application of recommender systems and machine learning and discuss future research issues.

Original language	English
Title of host publication	VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems
Editors	Paul Grunbacher
Place of Publication	New York, NY
Publisher	Association of Computing Machinery
Pages	1-8
Number of pages	8
ISBN (Electronic)	978-1-4503-8824-5
DOIs	https://doi.org/10.1145/3442391.3442408
Publication status	Published - Feb 2021
Event	15th International Working Conference on Variability Modelling of Software-Intensive Systems - Virtual from the IMC Krems University of Applied Science, Virtuell, Austria Duration: 9 Feb 2021 → 11 Feb 2021 https://vamos2021.fh-krems.ac.at

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	15th International Working Conference on Variability Modelling of Software-Intensive Systems
Abbreviated title	VaMoS 21
Country/Territory	Austria
City	Virtuell
Period	9/02/21 → 11/02/21
Internet address	https://vamos2021.fh-krems.ac.at

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3442391.3442408Licence: Unspecified

Cite this

Felfernig, A., Le, V-M., Popescu, A., Uta, M., Tran, T., & Atas, M. (2021). An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration. In P. Grunbacher (Ed.), VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems (pp. 1-8). Article 16 (ACM International Conference Proceeding Series). Association of Computing Machinery. https://doi.org/10.1145/3442391.3442408

An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration. / Felfernig, Alexander ; Le, Viet-Man ; Popescu, Andrei et al.
VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems. ed. / Paul Grunbacher. New York, NY: Association of Computing Machinery, 2021. p. 1-8 16 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Felfernig, A , Le, V-M , Popescu, A, Uta, M, Tran, T & Atas, M 2021, An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration. in P Grunbacher (ed.), VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems., 16, ACM International Conference Proceeding Series, Association of Computing Machinery, New York, NY, pp. 1-8, 15th International Working Conference on Variability Modelling of Software-Intensive Systems, Virtuell, Austria, 9/02/21. https://doi.org/10.1145/3442391.3442408

Felfernig A , Le V-M , Popescu A, Uta M, Tran T, Atas M. An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration. In Grunbacher P, editor, VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems. New York, NY: Association of Computing Machinery. 2021. p. 1-8. 16. (ACM International Conference Proceeding Series). doi: 10.1145/3442391.3442408

Felfernig, Alexander ; Le, Viet-Man ; Popescu, Andrei et al. / An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration. VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems. editor / Paul Grunbacher. New York, NY : Association of Computing Machinery, 2021. pp. 1-8 (ACM International Conference Proceeding Series).

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An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration

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