@article {854, title = {Using Prediction Confidence Factors to Enhance Collaborative Filtering Recommendation Quality}, journal = {Technologies}, volume = {13}, year = {2025}, pages = {181}, abstract = {

Recommender systems suggest items that users are likely to accept by predicting ratings for items they have not already rated. Collaborative filtering is a widely used method that produces these predictions, based on the ratings of similar users, termed as near neighbors. However, in many cases, prediction errors occur and, therefore, the recommender system ends up either recommending unwanted products or missing out on products the user would actually desire. As a result, the quality of the recommendations that are produced is of major importance. In this paper, we introduce an advanced collaborative filtering recommendation algorithm that upgrades the quality of the recommendations that are produced by considering, along with the rating prediction value of the items computed by the plain collaborative filtering procedure, a number of confidence factors that each rating prediction fulfills. The presented algorithm maintains high recommendation coverage, and can be applied to every collaborative filtering dataset, since it is based only on the very basic information. Based on the application of the algorithm on widely used recommender systems datasets, the proposed algorithm significantly upgrades the recommendation quality, surpassing the performance of state-of-the-art research works that also consider confidence factors.

}, keywords = {Algorithm, collaborative filtering, prediction confidence factors, recommendation quality, Recommender Systems}, issn = {2227-7080}, doi = {https://doi.org/10.3390/technologies13050181}, url = {https://doi.org/10.3390/technologies13050181}, author = {Dionisis Margaris and Spiliotopoulos, Dimitris and Sgardelis, Kiriakos and Costas Vassilakis} } @conference {830, title = {A User Interface for Tuning QoS parameters in Recommendation-Based Business Process Scenario Adaptation}, booktitle = {Proceedings of the 19th International Conference on Web Information Systems and Technologies (WEBIST 2023)}, year = {2023}, abstract = {

The Web Services Business Process Execution Language (BPEL) is a special-purpose language that orchestrates web services into a high-level business process. A typical BPEL scenario contains invocations to preselected web services, along with their parameters. However, many recent research works support dynamic service selection, based on user-set policies and criteria. Furthermore, users may request a service recommendation, in which case functionally equivalent service offerings by different providers will be considered by the personalization module. Along with the recommendation request, users provide the policy parameters, which include minimum and maximum bounds for the non-functional attributes concerning the service, and the system exploits these bounds to select and use the optimal candidate services. However, in many real-life cases, a person will accept/purchase a product or a service that exceeds the threshold(s) that initially he/she has set, e.g. if the overhead is marginal or the offer is deemed appealing, or no satisfactory service candidates are identified using the initial settings. In this paper, we present and evaluate a specialized User Interface that allows the user to review service candidates marginally exceeding the specified bounds, and consider them while making the final service selection.

}, keywords = {adaptation, business processes, Personalisation, Recommendation, Recommender Systems, UI, Web services, WS-BPEL}, author = {Kiriakos Sgardelis and Dionisis Margaris and Dimitris Spiliotopoulos and Costas Vassilakis} } @conference {800, title = {Understanding and mitigating banking trojans: From Zeus to Emotet}, booktitle = {Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, abstract = {

Banking Trojans came a long way in the past decade, and the recent case of Emotet showed their enduring relevance. The evolution of the modern computing landscape can be traced through Emotet and Zeus, both representative examples from the end of the past decade. As an example of earlier malware, Zeus only needed to employ simple anti-analysis techniques to stay undetected; while the more recent Emotet had to constantly evolve to stay a step ahead. Current host-based antimalware solutions face an increasing number of obstacles to perform their function. A multi-layer approach to network security is necessary for network-based intrusion response systems to secure modern networks of heterogeneous devices. A system based on a combination of a graphical network security model and a game theoretic model of cyber attacks was tested on a testbed with Windows machines infected with Trojans; experimental results showed that the proposed system effectively blocked Trojans{\textquoteright} network communications effectively preventing data leakage and yielding encouraging results for future work.

}, keywords = {Cyber security, Graphical security models, Intrusion response systems, Malware analysis, Reverse engineering}, author = {Grammatikakis, Konstantinos-Panagiotis and Koufos, Ioannis and Kolokotronis, Nicholas and Costas Vassilakis and Shiaeles, Stavros} } @conference {802, title = {A User Interface for Personalising WS-BPEL Scenarios}, booktitle = {Proceedings of the 2021 International Conference on Human-Computer Interaction: HCI in Business, Government and Organizations}, year = {2021}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {

Due to the huge volume of web services available, both locally and in the cloud, the performance of users and systems need significant research attention. Since WS-BPEL is the dominant language for orchestrating individual web services into business processes, by composing WS-BPEL scripts/scenarios, graphical notations facilitating WS-BPEL design can be extremely useful. Current user interfaces allow WS-BPEL designers not only to invoke selected web services, but also to explicitly ask for recommendations. Then, the user interface appends the services achieving the highest score, according to the attributes{\textquoteright} importance, set by the designer, to their WS-BPEL scenario. However, since the final selection is produced automatically, rather than relying on the designers{\textquoteright} choices, many times, from a personalisation point of view, the adaptation fails. This work reports on the design, development and user evaluation of a user interface that incorporates functionalities that support the designers{\textquoteright} selection performance, thereby upgrading the personalisation level of the WS-BPEL scenarios, as well as the success of the adaptation.

}, keywords = {Personalisation, Recommender Systems, Usability, User evaluation, user interface, Web services, WS-BPEL scenarios}, isbn = {978-3-030-77750-0}, doi = {https://doi.org/10.1007/978-3-030-77750-0_25}, author = {Dionisis Margaris and Spiliotopoulos, Dimitris and Vasilopoulos, Dionysios and Costas Vassilakis} } @conference {785, title = {A User Interface for Personalized Web Service Selection in Business Processes}, booktitle = {Lecture Notes in Computer Science}, year = {2020}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {

Nowadays, due to the huge volume of information available on the web, the need for personalization is more than necessary. Choosing the right information for each user is as important as the way this information is presented to him or her. Currently, user-triggered recommendation requests for web services are implemented as an automatic recommendation based on parametric computation. This work reports on a specialized user interface for business processes, where writing code entails invocation of business process information. The paper presents the user interface design for Personalized Web Service Selection in Business Process scenario execution and the user evaluation by business process engineers.

}, keywords = {adaptation, business processes, personalization, user interface, Web services, WS-BPEL}, doi = {10.1007/978-3-030-60152-2_41}, author = {Dionisis Margaris and Dimitris Spiliotopoulos and Costas Vassilakis and Gregory Karagiorgos} } @conference {DBLP:conf/pakdd/ChronisGAS18, title = {Unsupervised Disaggregation of Low Granularity Resource Consumption Time Series}, booktitle = {Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part II}, year = {2018}, pages = {558{\textendash}570}, doi = {10.1007/978-3-319-93037-4_44}, url = {https://doi.org/10.1007/978-3-319-93037-4_44}, author = {Pantelis Chronis and Giorgos Giannopoulos and Spiros Athanasiou and Spiros Skiadopoulos} } @article {margaris-csimq-2017, title = {Using Time Clusters for Following Users{\textquoteright} Shifts in Rating Practices}, journal = {Complex Systems Informatics and Modeling Quarterly}, volume = {13}, year = {2017}, abstract = {Users that enter ratings for items follow different rating practices, in the sense that, when rating items, some users are more lenient, while others are stricter. This aspect is taken into account by the most widely used similarity metric in user-user collaborative filtering, namely, the Pearson Correlation, which adjusts each individual user rating by the mean value of the ratings entered by the specific user, when computing similarities. However, a user{\textquoteright}s rating practices change over time, i.e. a user could start as strict and subsequently become lenient or vice versa. In that sense, the practice of using a single mean value for adjusting users{\textquoteright} ratings is inadequate, since it fails to follow such shifts in users{\textquoteright} rating practices, leading to decreased rating prediction accuracy. In this work, we address this issue by using the concept of dynamic averages introduced earlier and we extend earlier work by (1) introducing the concept of rating time clusters and (2) presenting a novel algorithm for calculating dynamic user averages and exploiting them in user-user collaborative, filtering implementations. The proposed algorithm incorporates the aforementioned concept and is able to follow more successfully shifts in users{\textquoteright} rating practices. It has been evaluated using numerous datasets, and has been found to introduce significant gains in rating prediction accuracy, while outperforming the dynamic average computation approaches that are presented earlier.}, keywords = {collaborative filtering, Dynamic Average, Rating Abstention Interval, Rating Time Clusters, Ratings{\textquoteright} Timestamps, Recommender Systems}, issn = {2255-9922}, doi = {10.7250/csimq.2017-13.02}, author = {Dionisis Margaris and Costas Vassilakis} } @conference {bampatzia2016a, title = {The use of semantics in the CrossCult H2020 project}, booktitle = {Proceedings of the second International KEYSTONE Conference, (IKC2016)}, year = {2016}, pages = {190{\textendash}195}, abstract = {CrossCult is a newly started project that aims to make reflective history a reality in the European cultural context. In this paper we examine how the project aims to take advantage of advances in semantic technologies in order to achieve its goals. Specifically, we see what the quest for reflection is and, through practical examples from two of the project{\textquoteright}s flagship pilots, explain how semantics can assist in this direction}, doi = {https://doi.org/10.1007/978-3-319-53640-8_17}, url = {https://link.springer.com/chapter/10.1007/978-3-319-53640-8_17}, author = {Stavroula Bampatzia and Omar Gustavo Bravo-Quezada and Angela Antoniou and Martin Lopez Nores and Manolis Wallace and Giorgos Lepouras and Costas Vassilakis} } @conference {bampatzia-smap16, title = {Using Social media to stimulate history reflection in cultural heritage}, booktitle = {Proceedings of Semantic and Social Media Adaptation and Personalization (SMAP) 2016}, year = {2016}, month = {10}, abstract = {CrossCult H2020 is a European project, the aim of which is the reflection of history in a cultural setting. In this paper, we describe how social media can be linked to cultural heritage and in particular how we can incorporate games, social networks, history reflection and culture. The paper presents the case study of one of the project pilots, to show how history reflection can be enhanced with the use of social networks.}, doi = {10.1109/SMAP.2016.7753390}, url = {https://ieeexplore.ieee.org/document/7753390/}, author = {Stavroula Bampatzia and Angela Antoniou and Giorgos Lepouras and Costas Vassilakis and Manolis Wallace} } @conference {gala2013, title = {User Profiling: Towards a Facebook Game that Reveals Cognitive Style}, booktitle = {Proceedings of the GALA 2013 conference}, year = {2013}, month = {10}, pages = {349{\textendash}353}, address = {Paris, FR}, abstract = {This paper presents an innovative approach based on social-network gaming, which will extract players? cognitive styles for personalization purposes. Cognitive styles describe the way individuals think, perceive and remember information and can be exploited to personalize user interaction. Questionnaires are usually employed to identify cognitive styles, a tedious process for most users. Our approach relies on a Facebook game for discovering potential visitors? cognitive styles with an ultimate goal of enhancing the overall visitors{\textquoteright} experience in the museum. By hosting such a game on the museum?s webpage and on Facebook, the museum aims to attract new visitors, as well as to support the user profiling process.}, doi = {10.1007/978-3-319-12157-4_28}, author = {Angela Antoniou and Ioanna Lykourentzou and Rompa, J. and Tobias, E. and Giorgos Lepouras and Costas Vassilakis and Y. Naudet} } @conference {katifori2008b, title = {Using Spreading Activation through Ontologies to Support Personal Information Management}, booktitle = {Proceedings of CSKGOI, within IUI 2008}, year = {2008}, month = {1}, abstract = {Recent research in the domain of Personal Information Management has recognized the need for a paradigm shift towards a more activity-oriented system. Ontologies, as semantic networks with a structure not dissimilar to the one used by the human brain for storing long-term knowledge, may be very useful as the basis of such a system. This work proposes the use of spreading activation over ontologies in order to provide to a task-based system and its associated tools with methods to record semantics related to documents and tasks and to support user context inference.}, url = {http://ceur-ws.org/Vol-323/paper05.pdf}, author = {Akrivi Katifori and Costas Vassilakis and Alan Dix} } @conference {1992-spiliopoulou-parle, title = {Using Parallelism and Pipeline for the Optimisation of Join Queries}, booktitle = {PARLE {\textquoteright}92: Proceedings of the 4th International PARLE Conference on Parallel Architectures and Languages Europe}, year = {1992}, month = {6}, pages = {279{\textendash}294}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {London, UK}, abstract = {In this study we present a technique for the parallel optimisation of join queries, that uses the offered coarse-grain parallelism of the underlying architecture in order to reduce the CPU-bound optimisation overhead. The optimisation technique performs an almost exhaustive search of the solution space for small join queries and gradually, as the number of joins increases, it diverges towards iterative improvement. This technique has been developed on a low-parallelism transputer-based architecture, where its behaviour is studied for the optimisation of queries with many tenths of joins.}, isbn = {3-540-55599-4}, doi = {10.1007/3-540-55599-4_94}, author = {M. Spiliopoulou and M. Hatzopoulos and Costas Vassilakis} }