Publications
Export 15 results:
Author Title Type [ Year
] Filters: Keyword is Recommender Systems [Clear All Filters]
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2023. Disruptive Technologies for Parliaments: A Literature Review. Future Internet. 15:66.
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2023. Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets. Big Data and Cognitive Computing. 7:59.
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2023. A User Interface for Tuning QoS parameters in Recommendation-Based Business Process Scenario Adaptation. Proceedings of the 19th International Conference on Web Information Systems and Technologies (WEBIST 2023).
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2022. On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets. Information. 13:302.
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2021. On Addressing the Low Rating Prediction Coverage in Sparse Datasets Using Virtual Ratings. SN Computer Science. 2:255.
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2021. Identifying Reliable Recommenders in Users' Collaborating Filtering and Social Neighbourhoods. Lecture Notes in Social Networks. :51–76.
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2021. A User Interface for Personalising WS-BPEL Scenarios. Proceedings of the 2021 International Conference on Human-Computer Interaction: HCI in Business, Government and Organizations.
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2020. An Adaptive Social Network-Aware Collaborative Filtering Algorithm for Improved Rating Prediction Accuracy. IEEE Access. 8:68301–68310.
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2020. An Algorithm for Density Enrichment of Sparse Collaborative Filtering Datasets Using Robust Predictions as Derived Ratings. Algorithms. 13:174.
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2020. A Fine-grained Social Network Recommender System. Social Network Analysis and Mining. 10(8)
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2020. Improving collaborative filtering’s rating prediction coverage in sparse datasets by exploiting the “friend of a friend” concept. International Journal of Big Data Intelligence. 7(1)
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2020. What makes a review a reliable rating in recommender systems? Information Processing & Management. 57(6):102304.
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2019. Handling uncertainty in social media textual information for improving venue recommendation formulation quality in social networks. Social Network Analysis and Mining. 9:64.
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2018. Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems. Informatics. 5:21pages.
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2017. Using Time Clusters for Following Users’ Shifts in Rating Practices. Complex Systems Informatics and Modeling Quarterly. 13