Publications
Export 11 results:
Author Title Type [ Year
] Filters: Author is Dimitris Spiliotopoulos and Keyword is Recommender Systems [Clear All Filters]
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2026. Optimizing Collaborative Filtering in Very Sparse Datasets: a Confidence-based Approach. Proceedings of the 2026 International Conference on Information, Intelligence, Systems and Applications.
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2024. Improving Recommendation Quality in Collaborative Filtering by Including Prediction Confidence Factors. Proceedings of the 20th International Conference on Web Information Systems and Technologies (WEBIST 24).
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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. Identifying Reliable Recommenders in Users' Collaborating Filtering and Social Neighbourhoods. Lecture Notes in Social Networks. :51–76.
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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. What makes a review a reliable rating in recommender systems? Information Processing & Management. 57(6):102304.