@mastersthesis {848, title = {Development and evaluation of a team formation algorithm for gaming environments}, year = {2021}, month = {10/2021}, pages = {48}, type = {Undergraduate}, abstract = {

In the context of multiplayer online games, but in many other group activities that entail collaboration between user, appropriate group formation is a critical issue. Groups should be formulated in a way that on the one hand user collaboration (or collaboration avoidance) preferences are respected, and on the other hand collaboration potential and productivity of groups is maximized.


In the current thesis, we consider an internet-based collaboration environment, where users work in pairs and, after their collaboration, each of them rates the quality of work and the quality of collaboration of his/her partner. Moreover, users have the option to express a positive, negative or neutral opinion towards the possibility of cooperating with individual users. For such an environment, we have developed an algorithm that employs linear
programming techniques, in order to create an optimal user pair formulation, considering the ratings that users have assigned to other users and collaboration intention statements. We present in detail the system structure, the algorithms and techniques employed, and we analyze the performance of the system in terms of the time needed to formulate user pair assignments
in various indicative cases. Finally, potential future extensions are outlined.

}, keywords = {glpk, Java, linear programming, maximization problem, scpsolver, User groups, μέθοδος simplex method}, author = {Iasonas Topalidis} } @conference {Katifori2008133, title = {Selected results of a comparative study of four ontology visualization methods for information retrieval tasks}, booktitle = {Proceedings of the 2nd International Conference on Research Challenges in Information Science, RCIS 2008}, year = {2008}, note = {cited By (since 1996) 0}, month = {6}, pages = {133-140}, abstract = {The need for effective ontology visualization for design, management and browsing has arisen as a result of the progress in the areas of Semantic Web and Personal Information Management. There are several ontology visualizations available through existing ontology management tools, but not as many evaluations to determine their advantages and disadvantages and their suitability for various ontologies and user groups. This work presents selected results of an evaluation of four visualization methods in ProtΓ{\textcopyright}gΓ{\textcopyright}.}, keywords = {Communication, Comparative studies, Information management, Information retrieval, Information science, Information services, Information theory, Management, Management information systems, Ontology, Ontology managements, Personal Information managements, Semantic Web, Telecommunication services, User groups, User interfaces, Visualization, visualization methods}, doi = {10.1109/RCIS.2008.4632101}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-57349172797\&partnerID=40\&md5=1f36a9a0febecb929cd7904c84004143}, author = {Akrivi Katifori and Elena Torou and Costas Vassilakis and Giorgos Lepouras and C. Halatsis} } @conference {Golemati200662, title = {A context-based adaptive visualization environment}, booktitle = {Proceedings of the International Conference on Information Visualisation}, year = {2006}, note = {cited By (since 1996) 0}, month = {7}, pages = {62-67}, abstract = {Digital libraries and historical archives are increasingly employing visualization systems to facilitate the information retrieval and knowledge extraction tasks of their users. Typically, each organization employs a single visualization system, which may not suit best the needs of certain user groups, specific tasks, or properties of document collections to be visualized. In this paper we present a context-based adaptive visualization environment, which embeds a set of visualization methods into a visualization library, from which the most appropriate one is selected for presenting information to the user. Methods are selected by examining parameters related to the user profile, system configuration and the set of data to be visualized, and employing a set of rules to assess the suitability of each method. The presented environment additionally monitors user behavior and preferences to adapt the visualization method selection criteria. Β{\textcopyright} 2006 IEEE.}, keywords = {(PL) properties, Adaptive systems, Adaptive visualization, Behavioral research, Digital libraries, document collections, Extraction, Information analysis, Information science, Information services, Information systems, Information visualization, Knowledge extraction, Libraries, Retrieval (MIR), Search engines, Selection criterion, Set of rules, Solvent extraction, Specific tasks, System configurations, User behaviors, User groups, user profiling, Visualization, visualization methods, Visualization systems}, doi = {10.1109/IV.2006.5}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-45149121827\&partnerID=40\&md5=ec45ad555b132faaf0bd2ca53e3292dc}, author = {M. Golemati and C. Halatsis and Costas Vassilakis and Akrivi Katifori and Giorgos Lepouras} }