Publications
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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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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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2015. A Collaborative Filtering Algorithm with Clustering for Personalized Web Service Selection in Business Processes. Proceedings of RCIS 2015.
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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. 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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2021. Augmenting Black Sheep Neighbour Importance for Enhancing Rating Prediction Accuracy in Collaborative Filtering. Applied Sciences. 11:8369.
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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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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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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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2020. A User Interface for Personalized Web Service Selection in Business Processes. Lecture Notes in Computer Science.
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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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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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2016. Recommendation information diffusion in social networks considering user influence and semantics. Social Network Analysis and Mining. 6:108.
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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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2017. Using Time Clusters for Following Users’ Shifts in Rating Practices. Complex Systems Informatics and Modeling Quarterly. 13
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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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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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2022. On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets. Information. 13:302.
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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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2017. Knowledge-Based Leisure Time Recommendations in Social Networks. Current Trends on Knowledge-Based Systems. :23–48.
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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).