@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 = {<p>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.</p>
},
	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 {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 = {<p>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.</p>
},
	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}
}
@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}
}
