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Investigating and counteracting popularity bias in group recommendations
(Elsevier, 2021)
Popularity bias is an undesirable phenomenon associated with recommendation algorithms where popular items tend to be suggested over long-tail ones, even if the latter would be of reasonable interest for individuals. Such ...
Treating adverse effects of blockbuster bias on beyond-accuracy quality of personalized recommendations
(Elsevier, 2022)
Collaborative filtering recommendation algorithms are vulnerable against the popularity bias, including the most popular items repeatedly into the produced ranked lists. However, the research on popularity bias focuses ...
Novel automatic group identification approaches for group recommendation
(Elsevier, 2021)
Group recommender systems are specialized in suggesting preferable products or services to a group of users rather than an individual by aggregating personal preferences of group members. In such expert systems, the initial ...
An entropy empowered hybridized aggregation technique for group recommender systems
(Elsevier, 15.03.2021)
Group recommender systems aim to suggest appropriate products/services to a group of users rather than individuals. These recommendations rely solely on determining group preferences, which is accomplished by an aggregation ...
Binary multicriteria collaborative filtering
(Scientific and technological research council of turkey, 30.11.2020)
Collaborative filtering is specialized in suggesting appropriate products and services to the users concerning personal characteristics and past preferences without requiring any effort of users. It might be more efficient ...
New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems
(MDPI, 20.01.2021)
Software collaboration platforms where millions of developers from diverse locations can contribute to the common open source projects have recently become popular. On these platforms, various information is obtained from ...
A multiclass hybrid approach to estimating software vulnerability vectors and severity score
(Elsevier, 2021)
Classifying detected software vulnerabilities is an important process. However, the metric values of security vectors are manually determined by humans, which takes time and may introduce errors stemming from human nature. ...
Open Source Software Development Challenges: A Systematic Literature Review on GitHub
(IGI GLOBAL, 01.11.2021)
GitHub is the most common code hosting and repository service for open-source software (OSS) projects. Thanks to the great variety of features, researchers benefit from GitHub to solve a wide range of OSS development ...
IESR: Instant Energy Scheduling Recommendations for Cost Saving in Smart Homes
(IEEE, 10.05.2022)
The exponential increase in energy demands continuously causes high price energy tariffs for domestic and commercial consumers. To overcome this problem, researchers strive to discover effective ways to reduce peak-hour ...
Evaluating unfairness of popularity bias in recommender systems: A comprehensive user-centric analysis
(Elsevier, 2022)
The popularity bias problem is one of the most prominent challenges of recommender systems,
i.e., while a few heavily rated items receive much attention in presented recommendation
lists, less popular ones are underrepresented ...