Publications
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] Title Type Year Filters: Author is Dionisis Margaris [Clear All Filters]
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2021. Augmenting Black Sheep Neighbour Importance for Enhancing Rating Prediction Accuracy in Collaborative Filtering. Applied Sciences. 11:8369.
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2016. Recommendation information diffusion in social networks considering user influence and semantics. Social Network Analysis and Mining. 6:108.
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2018. Enhancing Rating Prediction Quality Through Improving the Accuracy of Detection of Shifts in Rating Practices. Lecture Notes in Computer Science. 10940 (LNCS):151–191.
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2019. Improving Collaborative Filtering’s Rating Prediction Quality by Exploiting the Item Adoption Eagerness Information. Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence.
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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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2017. Improving Collaborative Filtering’s Rating Prediction Quality by Considering Shifts in Rating Practices. Proceedings of the 19th IEEE International Conference on business informatics (CBI17).
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2015. A Hybrid Framework for WS-BPEL Scenario Execution Adaptation, Using Monitoring and Feedback Data. Proceedings of the 30th ACM/SIGAPP Symposium On Applied Computing, SOAP track.
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2020. Improving collaborative filtering’s rating prediction accuracy by considering users’ dynamic rating variability. International Journal of Big Data Intelligence. 7(2)
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2020. A User Interface for Personalized Web Service Selection in Business Processes. Lecture Notes in Computer Science.
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2017. Knowledge-Based Leisure Time Recommendations in Social Networks. Current Trends on Knowledge-Based Systems. :23–48.
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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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2022. On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets. Information. 13:302.
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2015. On Replacement Service Selection in WS-BPEL Scenario Adaptation. Proceedings of the 8th IEEE International Conference on Service Oriented Computing & Applications (SOCA 2015).
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2015. An integrated framework for adapting WS-BPEL scenario execution using QoS and collaborative filtering techniques. Science of Computer Programming. 98:707–734.
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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. An Algorithm for Density Enrichment of Sparse Collaborative Filtering Datasets Using Robust Predictions as Derived Ratings. Algorithms. 13:174.
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2016. Pruning and Aging for User Histories in Collaborative Filtering. Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence.
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2017. Using Time Clusters for Following Users’ Shifts in Rating Practices. Complex Systems Informatics and Modeling Quarterly. 13
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2019. Social Relations versus Near Neighbours: Reliable Recommenders in Limited Information Social Network Collaborative Filtering for Online Advertising. Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019).
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2022. Anchoring Effect Mitigation for Complex Recommender System Design. Proceedings of the 2022 HCI International Conference.
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2013. Adapting WS-BPEL scenario execution using collaborative filtering techniques. IEEE 7th International Conference on Research Challenges in Information Science (RCIS).
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2016. Improving QoS Delivered by WS-BPEL Scenario Adaptation through Service Execution Parallelization. Proceedings of the 31st Annual ACM Symposium on Applied Computing. :1590-1596.
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2018. Improving Collaborative Filtering's Rating Prediction Coverage in Sparse Datasets by Exploiting User Dissimilarity. 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech).
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2020. What makes a review a reliable rating in recommender systems? Information Processing & Management. 57(6):102304.