Publications
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] Title Type Year Filters: Author is Dionisis Margaris [Clear All Filters]
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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.
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2017. Exploiting Internet of Things information to enhance venues' recommendation accuracy. Service Oriented Computing and Applications. todb:393–409.
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2017. Query personalization using social network information and collaborative filtering techniques. Future Generation of Computer Systems. Special Issue on Recommender Systems for Large-Scale Social Networks:440–450.
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2019. Improving Collaborative Filtering’s Rating Prediction Coverage in Sparse Datasets through the Introduction of Virtual Near Neighbors. Proceedings of the 10th International Conference on Information, Intelligence, Systems and Applications (IISA2019).
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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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2015. A Collaborative Filtering Algorithm with Clustering for Personalized Web Service Selection in Business Processes. Proceedings of RCIS 2015.
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2017. Enhancing User Rating Database Consistency Through Pruning. Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIV. LNCS, volume 10620:33–64.
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2018. Improving Collaborative Filtering's Rating Prediction Accuracy by Considering Users' Rating Variability. 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. An Adaptive Social Network-Aware Collaborative Filtering Algorithm for Improved Rating Prediction Accuracy. IEEE Access. 8:68301–68310.
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2017. Improving Collaborative Filtering's Rating Prediction Quality in Dense Datasets, by Pruning Old Ratings. Proceedings of the 22nd IEEE Symposium on Computers and Communications (ISCC17).
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2013. An integrated framework for QoS-based adaptation and exception resolution in WS-BPEL scenarios. Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC \textquotesingle13.
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2019. Improving Collaborative Filtering’s Rating Prediction Accuracy by Introducing the Common Item Rating Past Criterion. Proceedings of the 10th International Conference on Information, Intelligence, Systems and Applications (IISA2019).