Papers by Basilis Boutsinas
Quality of Life and Health Tourism: A Conceptual Roadmap of Enhancing Cognition and Well-Being
Springer proceedings in business and economics, 2023
A Conceptual Framework for Applying Social Signal Processing to Neuro-Tourism
Springer proceedings in business and economics, 2023
JOURNAL OF INTERNATIONAL MONEY, BANKING AND FINANCE
The interesting properties of scale-free and small-world networks recently observed have triggere... more The interesting properties of scale-free and small-world networks recently observed have triggered the attention of the research community to the study of real growing complex networks. In scale-free networks, most vertices are sparsely connected, while a few vertices are intensively connected to many others, indicating a “preferential linking” during growing. In small-world networks, the average length of the shortest path between two randomly chosen nodes is small. In this paper, we study the topological and dynamical properties of the network of shareholders (NOS) in 11593 different companies. Based on Graph Databases, we calculate all the well-known in the literature topological and dynamical properties of a network along with centrality measures of nodes of NOS, which quantify the role that a node plays in the overall structure of NOS. We prove that NOS is both a scale-free and smallworld network. An understanding of NOS helps in predicting the emergence of important new phenom...
Developmental Trauma and Neurocognition in Young Adults: A Systematic Review
EDULEARN Proceedings
The E-Tour Facilitator Platform Supporting an Innovative Health Tourism Marketing Strategy
Culture and Tourism in a Smart, Globalized, and Sustainable World
Health tourism is a special form of tourism that refers to international patients who wish to com... more Health tourism is a special form of tourism that refers to international patients who wish to combine diagnosis, prevention, or treatment with a holiday. In health tourism marketing, services are designed, produced, and promoted in the market to meet specific both health and tourism need or desires of the people who want and can accept them. In general, the rapid development of information and communication technologies (ICTs) in tourism sector has led to new touristic and thematic tourism products tailored to the preferences and characteristics of the tourists. The hotel industry could benefit from its cooperation with thematic tourism platforms to address the seasonality, expand its target audience, and enhance the effectiveness of its marketing strategy. Nevertheless, most tourism providers in Greece, being small family businesses, lack the necessary information and communication technologies (and inherent technologies) to become globally competitive. Given the growing trend in the interest in health tourism, this paper aims to present the case of “e-Tour Facilitator Platform,” an intelligent information system aiming at supporting an Innovative Health Tourism Strategy. The platform focuses on the end-users, namely the patients/tourists, matching their profile to characteristics of both medical and tourism services. It exploits state-of-the-art machine learning techniques in order both to help end-users to view/select the proper health tourism product (recommender system) with respect to their profile as well as to automatically handle their comments (text mining) for evaluating purposes.
Algorithms
Recommender systems aim to forecast users’ rank, interests, and preferences in specific products ... more Recommender systems aim to forecast users’ rank, interests, and preferences in specific products and recommend them to a user for purchase. Collaborative filtering is the most popular approach, where the user’s past purchase behavior consists of the user’s feedback. One of the most challenging problems in collaborative filtering is handling users whose previous item purchase behavior is unknown, (e.g., new users) or products for which user interactions are not available, (e.g., new products). In this work, we address the cold-start problem in recommender systems based on frequent patterns which are highly frequent in one set of users, but less frequent or infrequent in other sets of users. Such discriminant frequent patterns can distinguish one target set of users from all other sets. The proposed methodology, first forms different clusters of old users and then discovers discriminant frequent patterns for each different such cluster of users and finally exploits the latter to hallu...
Web Data Analytics in GDPR Compliance in Greek Hotel Industry and the Impact on Marketing
The reality of data privacy has changed for well. One of the most crucial cultural change busines... more The reality of data privacy has changed for well. One of the most crucial cultural change business is confronting with, is the need of systematic inclusion of privacy and data protection in every business process through technical and organizational measures.Every business in EU should ensure that clients' personal data are always handled in a GDPR compliant manner. General Data Protection Regulation enables business to develop a competitive advantage, given the unique opportunity to reinforce its privacy compliance posture and preserve the trust of its clients, while preserving their most valuable assets and reducing its exposure to risk.Today, any hotel with a website or social media presence already has access to amazing quantities of personal data. According to the Regulation, processing of personal data is legal if, inter alia, the data subject has consented to the processing of his or her personal data for one or more specific purposes. It is obvious that application of th...
Music analysis, i.e. using computers to analyze fully notated pieces of musical score, is one of ... more Music analysis, i.e. using computers to analyze fully notated pieces of musical score, is one of the most important research issues in computer music. Machine learning has played a crucial role in the computer music almost since its beginning. Recently, research in the field has focused on music mining. Data Mining is an emerging knowledge discovery process of extracting previously unknown, actionable information from very large scientific and commercial databases. Classification, clustering and association are the most well known data mining techniques. Data mining techniques are good candidates for music analysis. However, a proper music representation scheme is a prerequisite for their application. In this paper, we propose such a scheme for monophonic music representation as traditional data sets suitable for common data mining algorithms. We also present experimental results that demonstrate how the proposed representation technique is useful and helpful for analyzing and under...
2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA), 2019
There is a growing interest in the offering of novel alternative choices to users of recommender ... more There is a growing interest in the offering of novel alternative choices to users of recommender systems. These recommendations should match the target query while at the same time they should be diverse with each other in order to provide useful alternatives to the user, i.e., novel recommendations. In this paper, the problem of extracting novel recommendations, under the similarity-diversity trade-off, is modeled as a facility location problem. The results from tests in the benchmark Travel Case Base were satisfactory when compared to well-known recommender techniques, in terms of both similarity and diversity. It is shown that the proposed method is flexible enough, since a parameter of the adopted facility location model constitutes a regulator for the trade-off between similarity and diversity. Also, our work can broaden the perspectives of the interaction and combination of different scientific fields in order to achieve the best possible results.
This chapter discusses on an ontology developed for a case based reasoning system that aims at th... more This chapter discusses on an ontology developed for a case based reasoning system that aims at the support of people facing autism spectrum disorders (ASD). PAVEFS is an intelligent information system designed for the personalized provision of services for the diagnosis and the care of individuals of various ages and types of autism. The objective of PAVEFS is to lead to best practices' models and to provide access to information regarding the care procedures of individuals with ASD. PAVEFS is based both on scientific knowledge of autism and on practical information, acquired from experts and caregivers from various specializations, aiming at the creation of an extended basis of specialized and reliable information and at answering questions related to care procedures of children and adults facing ASD.
Do Hotels Care? A Proposed Smart Framework for the Effectiveness of an Environmental Management Accounting System Based on Business Intelligence Technologies
Culture and Tourism in a Smart, Globalized, and Sustainable World, 2021
Document clustering based on association rule mining
Recent Progress in Computational Sciences and Engineering, 2019
Proceedings of the International Conference on Knowledge Engineering and Ontology Development, 2009
Ontology merging/alignment is one of the most important tasks in ontology engineering. It is impo... more Ontology merging/alignment is one of the most important tasks in ontology engineering. It is imposed by the decentralized nature of both the WWW and the Semantic Web, where heterogeneous and incompatible ontologies can be developed by different communities. Usually, ontology merging/alignment is based on an ontology mapping that has been established in a previous phase. In this paper, we define a new problem within the alignment process: the problem of detecting and then updating only interesting parts of an ontology, based on the knowledge included in another one. To this end, we define and evaluate a number of different measures of interestingness of parts of ontologies. We also present experimental results for their evaluation on test ontologies.
On solving the multiple p-median problem based on biclustering
Operational Research, 2019
In this paper, we discuss the multiple p-median problem (MPMP), an extension of the original p-me... more In this paper, we discuss the multiple p-median problem (MPMP), an extension of the original p-median problem and present several potential applications. The objective of the well-known p-median problem is to locate p facilities in order to minimize the total distance between demand points and facilities. Each demand point should be covered by its closest facility. In the MPMP, each demand point should be covered by more than one facilities closer to it, represented in total by the mc parameter. The MPMP can be applied to various location problems, e.g. the provision of emergency services where alternative facilities need to hedge against the unavailability of the primary facility, as well as to other domains, e.g. recommender systems where it may be desirable to respond to each user query with more than one available choice that satisfy their preferences. We efficiently solve the MPMP by using a biclustering heuristic, which creates biclusters from the distance matrix. In the proposed approach, a bicluster represents a subset of demand points covered by a subset of facilities. The heuristic selects appropriate biclusters taking into account the objective of the problem. Based on experimental tests performed in known benchmark problems, we observed that our method provides solutions slightly inferior to the optimal ones in significantly less computational time when compared to the CPLEX optimizer. In larger test instances, our method outperforms CPLEX both in terms of computational time and solution quality, when a time bound of 1 h is set for obtaining a solution.
Proceedings of the 11th International Conference on Enterprise Information, 2009
Ontology mapping is one of the most important processes in ontology engineering. It is imposed by... more Ontology mapping is one of the most important processes in ontology engineering. It is imposed by the decentralized nature of both the WWW and the Semantic Web, where heterogeneous and incompatible ontologies can be developed by different communities. Ontology mapping can be used to establish efficient information sharing by determining correspondences among such ontologies. The ontology mapping techniques presented in the literature are based on syntactic and/or semantic heuristics. In almost all of them, user intervention is required. In this paper, we present a new ontology mapping technique which, given two input ontologies, is able to map concepts in one ontology onto those in the other, without any user intervention. It is based on association rule mining applied to the concept hierarchies of the input ontologies. We also present experimental results that demonstrate the accuracy of the proposed technique.
Analysis of epileptic magnetoencephalogram dynamics through clustering algorithms
2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628)
We propose a novel method for the analysis of the magnetoencephalogram (MEG) of epileptic patient... more We propose a novel method for the analysis of the magnetoencephalogram (MEG) of epileptic patients. The proposed method was based on the reconstruction of the phase space from the one-dimension signals to higher-dimension phase space. An especially developed clustering algorithm was applied on the reconstructed data in order to investigate the distribution of epileptic MEG dynamics in higher order reconstructed phase spaces.
On managing nonmonotonic transitive relationships
Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence
ABSTRACT Efficient representation of knowledge, under a multiple inheritance scheme with exceptio... more ABSTRACT Efficient representation of knowledge, under a multiple inheritance scheme with exceptions, plays an important role in artificial intelligence. Fast verification of the existence of a transitive relationship in such a hierarchy is of great importance. This paper presents an efficient algorithm for computing transitive relationships with exceptions. It is based on a known transitive closure compression technique that uses a labeled spanning tree of a directed acyclic graph. It is a very fast algorithm compared to graph-search algorithms that solve the same problem, without sacrificing some desirable properties that nonmonotonic multiple inheritance schemes should, in general, possess. Moreover it satisfies low storage requirements.
Splitting Data in Decision Trees Using the New False-Positives Criterion
Lecture Notes in Computer Science, 2004
... Page 7. 180 Basilis Boutsinas and Ioannis X. Tsekouronas in terms of their physical character... more ... Page 7. 180 Basilis Boutsinas and Ioannis X. Tsekouronas in terms of their physical characteristics. The MONK's Problem data set, having 432 instances described by 8 attributes, describes an artificial domain over the same attribute space. ...
Belief Revision in nonmonotonic multiple inheritance using Weighted Inheritance Networks
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Papers by Basilis Boutsinas