@article {820, title = {Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets}, journal = {Big Data and Cognitive Computing}, volume = {7}, year = {2023}, month = {mar}, pages = {59}, abstract = {

Collaborative filtering has proved to be one of the most popular and successful rating prediction techniques over the last few years. In collaborative filtering, each rating prediction, concerning a product or a service, is based on the rating values that users that are considered {\textquotedblleft}close{\textquotedblright} to the user for whom the prediction is being generated have given to the same product or service. In general, {\textquotedblleft}close{\textquotedblright} users for some user u correspond to users that have rated items similarly to u and these users are termed as {\textquotedblleft}near neighbors{\textquotedblright}. As a result, the more reliable these near neighbors are, the more successful predictions the collaborative filtering system will compute and ultimately, the more successful recommendations the recommender system will generate. However, when the dataset{\textquoteright}s density is relatively low, it is hard to find reliable near neighbors and hence many predictions fail, resulting in low recommender system reliability. In this work, we present a method that enhances rating prediction quality in low-density collaborative filtering datasets, by considering predictions whose features are associated with high prediction accuracy as additional ratings. The presented method{\textquoteright}s efficacy and applicability are substantiated through an extensive multi-parameter evaluation process, using widely acceptable low-density collaborative filtering datasets.

}, keywords = {collaborative filtering, Evaluation, low density datasets, personalization, rating prediction quality, Recommender Systems, reliability}, doi = {10.3390/bdcc7020059}, url = {https://www.mdpi.com/2504-2289/7/2/59}, author = {Dionisis Margaris and Costas Vassilakis and Dimitris Spiliotopoulos and Stefanos Ougiaroglou} } @article {782, title = {Data-Assisted Persona Construction Using Social Media Data}, journal = {Big Data and Cognitive Computing}, volume = {4}, year = {2020}, month = {aug}, pages = {21}, abstract = {

User experience design and subsequent usability evaluation can benefit from knowledge about user interaction, types, deployment settings and situations. Most of the time, the user type and generic requirements are given or can be obtained and used to model interaction during the design phase. The deployment settings and situations can be collected through the needfinding phase, either via user feedback or via the automatic analysis of existing data. Personas may be defined using the aforementioned information through user research analysis or data analysis. This work utilizes an approach to activate an accurate persona definition early in the design cycle, using topic detection to semantically enrich the data that are used to derive the persona details. This work uses Twitter data from a music event to extract information that can be used to assist persona creation. A user study in persona construction compares the topic modelling metadata to a traditional user collected data analysis for persona construction. The results show that the topic information-driven constructed personas are perceived as having better clarity, completeness and credibility. Additionally, the human users feel more attracted and similar to such personas. This work may be used to model personas and recommend suitable ones to designers of other products, such as advertisers, game designers and moviegoers.

}, keywords = {Cultural Events, Persona, personalization, Topic Modelling, Usability, User Experience, User Interface Design}, doi = {10.3390/bdcc4030021}, author = {Dimitris Spiliotopoulos and Dionisis Margaris and Costas Vassilakis} } @article {781, title = {Multimodal Interaction: Correlates of Learners{\textquoteright} Metacognitive Skill Training Negotiation Experience}, journal = {Information}, volume = {11}, year = {2020}, month = {jul}, pages = {381}, abstract = {

Metacognitive training reflects knowledge, consideration and control over decision-making and task performance evident in any social and learning context. Interest in understanding the best account of effective (win-win) negotiation emerges in different social and cultural interactions worldwide. The research presented in this paper explores an extended study of metacognitive training system during negotiation using an embodied conversational agent. It elaborates on the findings from the usability evaluation employing 40 adult learners pre- and postinteraction with the system, reporting on the usability and metacognitive, individual- and community-level related attributes. Empirical evidence indicates (a) higher levels of self-efficacy, individual readiness to change and civic action after user-system experience, (b) significant and positive direct associations between self-efficacy, self-regulation, interpersonal and problem-solving skills, individual readiness to change, mastery goal orientation and civic action pre- and postinteraction and (c) gender differences in the perceptions of system usability performance according to country of origin. Theoretical and practical implications in tandem with future research avenues are discussed in light of embodied conversational agent metacognitive training in negotiation.

}, keywords = {big data, Cultural Events, Persona, personalization, Topic Modelling, Usability, User Experience, User Interface Design}, doi = {10.3390/info11080381}, author = {Dimitris Spiliotopoulos and Eleni Makri and Costas Vassilakis and Dionisis Margaris} } @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 {713, title = {TripMentor Project: scope and challenges}, booktitle = {Proceedings of the Workshop on Cultural Informatics, co-located with the 14th International Workshop On Semantic And Social Media Adaptation And Personalization (SMAP 2019)}, year = {2019}, abstract = {We present Tripmentor, a novel project, that is related to tourism in the region of Attica. The project has as main scope to provide rich media content to tourists through a web and mobile environment in two languages trying to guide them through alternative routes that include places of interest as well as organizations with offers to tourists. The project interconnects people with places and events in an automated manner trying to personalize on each tourist{\textquoteright}s personality. The challenges of the project are mainly technological as through the processes of the project a) automated information about venues must be collected, b) information about events related to venues must be fetched and finally c) data related to system users and mainly their profile should be discovered and created in order to offer a unique experience to each of them. We present the scope of the project as well as the challenges of its implementation.}, keywords = {cultural related information, geodata, personalization, social media, tourism, tripmentor}, url = {http://ceur-ws.org/Vol-2412/paper6.pdf}, author = {Costas Vassilakis and Vassilis Poulopoulos and Manolis Wallace and Angeliki Antoniou and George Lepouras}, editor = {Angeliki Antoniou and Manolis Wallace} } @conference {poulopoulos2018a, title = {The Effect of Social Media Trending Topics Related to Cultural Venues{\textquoteright} Content}, booktitle = {2018 13th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)}, year = {2018}, month = {sep}, publisher = {IEEE}, organization = {IEEE}, abstract = {Social media have gained the majority of attention on the Internet having an extreme number of daily visitors worldwide. The amount of information exchanged is vast, while users have become equally producers and consumers of data. Words like {\textquotedblleft}trending{\textquotedblright}, {\textquotedblleft}influencers{\textquotedblright}, {\textquotedblleft}likes{\textquotedblright} and {\textquotedblleft}viral{\textquotedblright} are in the daily agenda of data analyzers, as they are associated with factors that play an important role in the influence of social media content to its audience. These aspects are nowadays strongly taken into account by organizations that want to draw the public{\textquoteright}s attention to the content they deliver, and in this context cultural institutions have already started to take under great consideration not only their presence in social media, but also the exploitation of social media dynamics. In this paper we propose a method that can enable cultural venues to benefit from matches between their own content and ongoing discussions on social media. More specifically we extract trending topics that can be related semantically with the content of a cultural institute and examine how a venue can benefit by exploiting these matches. The proposed algorithm has been developed in the scope of the {\textquotedblleft}CrossCult{\textquotedblright} H2020 project, and has been experimentally tested by analyzing the case of Twitter in Greek language.}, keywords = {cultural informatics, cultural venues, personalization, social media, trending topics}, doi = {10.1109/SMAP.2018.8501878}, author = {Vassilis Poulopoulos and Costas Vassilakis and Manolis Wallace and Angela Antoniou and Giorgos Lepouras} } @article {Vassilakis_fgcs17, title = {exhiSTORY: Smart Exhibits That Tell Their Own Stories}, journal = {Future Generation of Computer Systems}, volume = {81}, year = {2018}, pages = {542-556}, abstract = {Museum exhibitions are designed to tell a story; this story is woven by curators and in its context a particular aspect of each exhibit, fitting to the message that the story is intended to convey, is highlighted. Adding new exhibits to the story requires curators to identify for each exhibit its aspects that fit to the message of the story and position the exhibit at the right place in the story thread. The availability of rich semantic information for exhibits, allows for exploiting the wealth of meanings that museum exhibits express, enabling the automated or semi-automated generation of practically countless stories that can be told. Personalization algorithms can then be employed to choose from these stories the ones most suitable for each individual user, based on the semantics of the stories and information within the user profile. In this work we examine how opportunities arising from technological advances in the fields of IoT and semantics can be used to develop smart, self-organizing exhibits that cooperate with each other and provide visitors with comprehensible, rich, diverse, personalized and highly stimulating experiences. These notions are included in the design of a system named exhiSTORY, which also exploits previously ignored information and identifies previously unseen semantic links. We present the architecture of the system and discuss its application potential.}, keywords = {Cultural heritage, IoT, personalization, Quality of Experience (QoE), Self-organizing exhibitions, semantics}, doi = {https://doi.org/10.1016/j.future.2017.10.038}, url = {https://www.sciencedirect.com/science/article/pii/S0167739X17324093}, author = {Costas Vassilakis and Vassilis Poulopoulos and Angela Antoniou and Manolis Wallace and Giorgos Lepouras and Martin Lopez Nores} } @article {Poulopoulos2018Heritage, title = {The personality of the influencers, the characteristics of qualitative discussions and their analysis for recommendations to cultural institutions}, journal = {Heritage}, volume = {1}, number = {2}, year = {2018}, month = {oct}, pages = {239-253}, abstract = {Social media usage is affecting peoples{\textquoteright} views through opinion sharing, a fact that has started to attract cultural institutions, as it is possible that this procedure can possibly be a part of a museum experience. As the main goal of a cultural institution is the maximization of senses stimulation, the device that is offered to the visitors{\textquoteright} hands everyday and every moment, becomes an important tool for the art spaces. In this notion we perform research on issues that can be of great importance for the museum{\textquoteright}s online presence and attraction. We focus on establishing the personality of influencers related to culture, as well as the characteristics of qualitative discussions on the social media. Crosscult Project is an EU funded project, that aims to spur a change in the way European citizens appraise History, and sets that basis of our research as the experiments are conducted within its scope of. Through the experimental procedure, we collect information in order to define the character of the influencer and the substances of a {\textquotedblleft}serious{\textquotedblright} conversation. {\textquotedblleft}Serious{\textquotedblright} conversations are regarded the ones in which a cultural organization can participate actively and benefit from the participation. We present the results of our experimental evaluation and analyze how cultural institutions can benefit from the outcomes of our research.}, keywords = {cultural informatics, digital humanities, personality traits, personalization, serious conversations, social media influencers, user modeling}, issn = {2571-9408}, doi = {10.3390/heritage1020016}, url = {https://doi.org/10.3390/heritage1020016}, author = {Vassilis Poulopoulos and Costas Vassilakis and Angela Antoniou and Giorgos Lepouras and Anastasios Theodoropoulos and Manolis Wallace} }