Browsing Bilgisayar Mühendisliği Bölümü Makale Koleksiyonu by Publisher "Elsevier"
Now showing items 1-8 of 8
-
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. ... -
A survey of smart home energy conservation techniques
(Elsevier, Mart, 2023)Smart homes are equipped with easy-to-interact interfaces, providing a more comfortable living environment and less energy consumption. There are currently satisfactory approaches proposed to deliver adequate comfort and ... -
Aggregating user preferences in group recommender systems: A crowdsourcing approach
(Elsevier, 2022)We present that group recommendations are similar to crowdsourcing, where the responses of different crowd workers are aggregated in the absence of ground truth. With this in mind, we mimic the use of the EM algorithm as ... -
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 ... -
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 ... -
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 ... -
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 ... -
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 ...