Publications
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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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2021. On Addressing the Low Rating Prediction Coverage in Sparse Datasets Using Virtual Ratings. SN Computer Science. 2:255.
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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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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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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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2023. Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets. Big Data and Cognitive Computing. 7:59.
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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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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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2022. On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets. Information. 13:302.
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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).
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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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2021. Identifying Reliable Recommenders in Users' Collaborating Filtering and Social Neighbourhoods. Lecture Notes in Social Networks. :51–76.
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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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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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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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2020. A User Interface for Personalized Web Service Selection in Business Processes. Lecture Notes in Computer Science.
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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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2020. Human behaviour in multimodal interaction: main effects of civic action and interpersonal and problem-solving skills. Journal of Ambient Intelligence and Humanized Computing. TBD:TBD.
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2004. A web browser for ISDN card phones. Journal of Internet Technology. 5:267-277.
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2001. Agents in Decentralised Information Ecosystems: The DIET Approach. Proccedings of the Symposium on Information Agents for E-Commerce, AISB Convention. :109–117.
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2001. Agents in Decentralised Information Ecosystems: The DIET Approach. Symposium on Information Agents for E-Commerce, AISB Convention.