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Found 18 papers, 3 papers with code
Sports Recommender Systems: Overview and Research Issues
Sports recommender systems receive an increasing attention due to their potential of fostering healthy living, improving personal well-being, and increasing performances in sport.
Solving Multi-Configuration Problems: A Performance Analysis with Choco Solver
In many scenarios, configurators support the configuration of a solution that satisfies the preferences of a single user.
Concentrating on the Impact: Consequence-based Explanations in Recommender Systems
Recommender systems assist users in decision-making, where the presentation of recommended items and their explanations are critical factors for enhancing the overall user experience.
FastDiagP: An Algorithm for Parallelized Direct Diagnosis
This algorithm extends FastDiag by integrating a parallelization mechanism that anticipates and pre-calculates consistency checks requested by FastDiag.
Conjunctive Query Based Constraint Solving For Feature Model Configuration
Feature model configuration can be supported on the basis of various types of reasoning approaches.
Perfect Match in Video Retrieval
This paper presents the first version of our video search system Perfect Match for the Video Browser Showdown 2023 competition.
Configuring Multiple Instances with Multi-Configuration
Configuration is a successful application area of Artificial Intelligence.
AI Techniques for Software Requirements Prioritization
Aspects such as limited resources, frequently changing market demands, and different technical restrictions regarding the implementation of software requirements (features) often demand for the prioritization of requirements.
CoreDiag: Eliminating Redundancy in Constraint Sets
For example, redundant constraints are specified which often increase both, the effort for calculating a solution and efforts related to knowledge base development and maintenance.
An Overview of Direct Diagnosis and Repair Techniques in the WeeVis Recommendation Environment
Constraint-based recommenders support users in the identification of items (products) fitting their wishes and needs.
Anytime Diagnosis for Reconfiguration
Many domains require scalable algorithms that help to determine diagnoses efficiently and often within predefined time limits.
Towards Utility-based Prioritization of Requirements in Open Source Environments
Requirements Engineering in open source projects such as Eclipse faces the challenge of having to prioritize requirements for individual contributors in a more or less unobtrusive fashion.
An Efficient Diagnosis Algorithm for Inconsistent Constraint Sets
Another example is the engineering phase of a configuration knowledge base where the underlying constraints can become inconsistent with a set of test cases.
Recommender Systems for Configuration Knowledge Engineering
The knowledge engineering bottleneck is still a major challenge in configurator projects.
KnowledgeCheckR: Intelligent Techniques for Counteracting Forgetting
In this paper, we provide an overview of the recommendation approaches integrated in KnowledgeCheckR.
Consistency-based Merging of Variability Models
Globally operating enterprises selling large and complex products and services often have to deal with situations where variability models are locally developed to take into account the requirements of local markets.
An Overview of Recommender Systems and Machine Learning in Feature Modeling and Configuration
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.
DirectDebug: Automated Testing and Debugging of Feature Models
Variability models (e. g., feature models) are a common way for the representation of variabilities and commonalities of software artifacts.
