Marketing is one of the industries most impacted by the rapid development of AI and its applications. This study, in particular, illuminates the significant field of content personalization, which is a highly successful marketing strategy. In a world where content personalization is increasingly implemented by e-commerce websites, movie platforms, music platforms, and even news websites, the practice of collecting personal information for content personalization has raised concerns among consumers, leading many to reject such practices. Individuals' beliefs and cultural characteristics play a significant role in their attitudes toward content personalization. Therefore, this study aims to explore the drivers that would lead someone to share their personal information for content personalization. However, rather than just examining this trade-off, the study seeks to gain a deeper understanding of the issue by exploring how these drivers are related to individual cultural characteristics. To explore consumers' opinions and the drivers that would motivate someone to share their personal information for content personalization, interviews were conducted with individuals from Northern Europe and Greece, who have different cultural characteristics. By examining the topic through personal experiences and perspectives, the study revealed that certain drivers are considered regardless of culture, while others are culturally specific, thus creating specific patterns for how individuals of different cultures think. This information can guide marketers, policymakers, and professionals in the field to align their practices with the diverse cultural characteristics of individuals.

The user experience in the e-commerce industry plays a pivotal role in retaining its customers.The competition between e-commerce business stores such as H&M or Kappahl is so fierce that improving the most basic functionalities, such as the current poor browsing experience ofe-commerce websites, can attract or retain even more internet users. Addressing this pressing issue in UX, an innovative solution addressing poor browsing experiences at e-commerce websites could be achieved through the personalization of the primary navigation menu. In an attempt to lay the foundations for further research in this niche, this paper addresses a design of a personalized navigation menu that renders recommended items based on the individual’s user patterns. The aim is to study the usability of such a digital artifact through the three usability metrics (Efficiency, Effectiveness and Satisfaction) in an attempt to understand if a personalized navigation menu is a viable solution for both practical implications and scientific research.

Ο παγκόσμιος ιστός αποτελεί μία τεράστια αποθήκη πληροφοριών και αναπτύσσεται με τάχιστους ρυθμούς, ενώ η ανθρώπινη ικανότητα να εντοπίζει, να επεξεργάζεται και να αντιλαμβάνεται τις παρεχόμενες πληροφορίες παραμένει πεπερασμένη. Οι μηχανές αναζήτησης διευκολύνουν την αναζήτηση στον παγκόσμιο ιστό και έχουν γίνει αναπόσπαστο κομμάτι της καθημερινής ζωής των χρηστών του διαδικτύου. Οι χρήστες όμως χαρακτηρίζονται από διαφορετικές ανάγκες, προτιμήσεις, ιδιαιτερότητες και κατά την πλοήγησή τους μπορεί να χάσουν τον στόχο της αναζήτησής τους. Η προσωποποίηση στον παγκόσμιο ιστό, δηλαδή η εξατομίκευση των παρεχόμενων αποτελεσμάτων, αποτελεί μία πολλά υποσχόμενη προσέγγιση για την λύση του πληροφοριακού υπερφόρτου, παρέχοντας κατάλληλα προσαρμοσμένες εμπειρίες πλοήγησης. Στα πλαίσια αυτής της διπλωματικής εργασίας αναπτύχθηκε μία μεθοδολογία για την προσωποποίηση των αποτελεσμάτων μίας μηχανής αναζήτησης ώστε αυτά να ανταποκρίνονται στις προτιμήσεις των χρηστών και στα διαιτολογικά τους χαρακτηριστικά. Η μεθοδολογία αναπτύχθηκε σε δύο μέρη: στο εκτός σύνδεσης τμήμα και στο συνδεδεμένο. Στο πρώτο με την χρησιμοποίηση των αρχείων πρόσβασης μίας μηχανής αναζήτησης και των διαιτολογικών χαρακτηριστικών των χρηστών, έγινε εξαγωγή πληροφορίας για τις προτιμήσεις των τελευταίων. Στην συνέχεια με την χρήση μίας οντολογίας που κατασκευάστηκε για τα πλαίσια της διπλωματικής αυτής εργασίας, έγινε σημασιολογική κατηγοριοποίηση των επιλογών των χρηστών και κατασκευάστηκαν τα προφίλ που τους χαρακτηρίζουν. Έπειτα με την χρήση ενός αλγορίθμου ομαδοποίησης οι χρήστες κατηγοριοποιήθηκαν με βάση τα διαιτολογικά τους χαρακτηριστικά και τις επιλογές τους στην μηχανή αναζήτησης. Στο συνδεδεμένο τμήμα ο αλγόριθμος προσωποποίησης εκμεταλλευόμενος την σημασιολογική αντιστοίχιση των αποτελεσμάτων της μηχανής αναζήτησης και τις ομάδες των χρηστών που δημιουργήθηκαν στο εκτός σύνδεσης τμήμα αναδιοργανώνει τα παρεχόμενα από την μηχανή αναζήτησης αποτελέσματα. Η αναδιοργάνωση γίνεται προωθώντας στις υψηλότερες θέσεις των αποτελεσμάτων της μηχανής αναζήτησης τα αποτελέσματα που ταιριάζουν καλύτερα με τις προτιμήσεις και τα χαρακτηριστικά της ομάδας στην οποία εντάσσεται ο χρήστης. Στο τέλος έγιναν πειράματα και εξακριβώθηκαν τα επιθυμητά αποτελέσματα για την προσωποποίηση σύμφωνα με τις σημασιολογικές ομάδες των χρηστών. / The World Wide Web has become a huge data repository and it keeps growing exponentially, whereas the human capability to find, process and understand the provided content remains constant. Search engines facilitate the search process in the World Wide Web and they have become an integral part of the web users' daily lives. However users who are characterized by different needs, preferences and special characteristics, navigate through large Web structures and may lost their goal of inquiry. Web personalization, i.e. the customization of the search engines’ returned results, is one of the most promising approaches for alleviating information overload providing tailored navigation experiences to Web users. The present dissertation presents the methodology which was implemented in order to personalize a search engine’s results for corresponding users’ preferences and dietary characteristics. This methodology was implemented in two parts: the offline and the online part. The first one uses a search engines’ log files and the dietary characteristics of the users in order to extract information for the latter preferences. Afterwards, with the use of an ontology which was created explicitly for this work, semantic profiling of users’ interests was achieved and their corresponding profiles were formed. Then with the use of a clustering algorithm, users’ categorization was made based on their dietary profiles and their preferences in the search engine. In the online part the methodology re-ranks the search engines’ results, based on the semantic characterization of those results and the users’ clusters which were created at the offline part. Re-ranking is achieved by placing those results which match better the interests and the characteristics of the user’s cluster at the top of the list of the search engines’ returned results. Experimental evaluation of the presented methodology shows that the expected objectives from the semantic users’ clustering in search engines are achievable.

在目前競爭激烈的商業環境中，個人化服務逐漸受到重視，並被公司視為增加競爭力的利器。此篇論文首先釐清個人化與客製化之間的關係，再將個人化相關的應用、技術及設計方法做一個基礎性的探討。 由於 “顧客” 是個人化的重心，此研究以三階段的Delphi研究方法探究哪些因素會影響顧客對於個人化服務的評價。許多個人化相關的研究是以公司的角度為出發點，但此研究則是以顧客的觀點來看台灣金融業的個人化服務。研究的兩個重點為：(1) 顧客對於台灣金融業目前的個人化服務評價為何？(2)台灣金融業在個人化服務方面最需要改進的部份為何？ 研究結果顯示，顧客是以一個cost-benefit viewpoint來評量企業所提供的個人化服務。對顧客而言，costs包括隱私上的損失及推銷和廣告所可能帶來的困擾。而benefits的主要來源則是好又準確的個人化服務。針對金融業來說，好又準確的個人化服務便是對個人需求經過精確的量身訂做後的資訊，在最適當的時間、地點以適當的管道提供給顧客。 研究結果也顯示，目前台灣金融業的個人化服務仍需要很大的努力與改進。此研究也整理出三個建議：(1)在個人化的過程中給顧客更多的掌控權；(2)尊重顧客的隱私權；(3)提供真正量身訂做的個人化服務，而不是把個人化當作推銷的藉口。 / Personalization is gaining increasing popularity among enterprises that strive to win a competitive edge by knowing and serving their customers better. This paper begins with an examination of the interdependency and inseparability between personalization and customization. An overview of personalization applications, technologies, and design techniques is then presented. As 'customer' is the theme of personalization, criteria that affect customers' acceptance and evaluation of personalization initiatives are then explored using a 3-stage Delphi method. Differed from many researches that examine personalization through the corporate / implementer's lenses, this study looks at personalization practices in Taiwan's financial industry – from a customer perspective. For such purpose, a financial personalization model is constructed from a customer standpoint. Two main questions to explore are: (1) how well do customers think personalization is being implemented in Taiwan's financial industry, and (2) which areas are in desperate need for improvements. Research results reveal that customers evaluate personalization efforts from a cost-benefit viewpoint. Potential costs include concession in privacy and concerns of possible promotion annoyance. On the other end of the scale, the main source of benefits is good and accurate personalization. In the case of financial industry, good personalization means precisely tailored information delivered at the right time and place. Unfortunately, the research also shows that currently the costs outweigh the benefits. Three suggestions are proposed: (1) give customers more control in the personalization process, (2) respect customers’ privacy, and (3) offer customers truly tailored information instead of an excuse to annoy customers with unwanted promotions.

La modélisation de l’électrophysiologie in silico a été un sujet de recherche important ces dernières décennies. Afin de pouvoir utiliser ces progrès importants dans les applications cliniques, il faut mettre en place des modèles macroscopiques qui peuvent être utilisés pour la planification et le guidage des procédures cliniques.L’objectif de cette thèse est de construire de tels modèles macroscopiques spécifiques à chaque patient pour le diagnostic et la prévision, dans le but d’améliorer la planification et le guidage de l’ablation par radio-fréquence (ARF) des patients souffrant de tachycardie ventriculaire (TV) après infarctus. Dans ce travail, nous avons proposé un cadre pour la personnalisation d’un modèle cardiaque 3D, le modèle de Mitchell-Schaeffer (MS), et nous avons évalué sa puissance prédictive dans plusieurs configurations de stimulation. Ceci a été réalisé sur des données ex vivo de cœurs porcins à l’aide d’images médicales et de données cartographiques optiques de l’épicarde. Ce cadre a ensuite été appliqué à un ensemble de données cliniques provenant d’imagerie hybride XMR et d’une procédure de cartographie électrophysiologique sur un patient souffrant d’insuffisance cardiaque.Ensuite, le modèle 3D MS a également été adapté pour simuler le comportement macroscopique structural de la fibrose près des cicatrices. La simulation d’une étude in silico de stimulation de TV en utilisant le modèle adapté personnalisé MS a été réalisée pour quantifier le risque de TV en termes de cartes d’inductibilité, de réentrées des modèles et de cartes de points de sortie. Une approche de modélisation pour l’ablation par RF fondée sur l’état de l’art a été proposée. Enfin, l’étude in silico de stimulation de TV a été appliquée aux données in vivo personnalisées des patients, qui ont suivi ce protocole. Ceci a permis une validation de la prévision in silico de TV post-infarctus par comparaison avec la TV clinique induite. Ler ôle de l’hétérogénéité spatiale des propriétés des tissus cardiaques estimés dans la genèse de TV ischémique a été évalué, ainsi que les caractéristiques des points de sortie, qui sont les candidats potentiels à l’ablation par RF. / Modelling cardiac electrophysiology for arrhythmias in silico has been an important research topic for the last decades. In order to translate this important progress into clinical applications, there is a requirement to make macroscopic models that can be used for the planning and guidance of clinical procedures. The objective of this thesis was to construct such macroscopic EP models specifict o each patient for study and prediction, in order to improve the planning and guidance of radio frequency ablation (RFA) the rapieson patients suffering from post infarction Ventricular Tachycardia (VT). In this work, we proposed a framework for the personalisation of a 3D cardiac EP model, the Mitchell-Schaeffer (MS) model, an devaluated its volumetric predictive power under various pacing scenarios.This was performed on ex vivo large porcine healthy heart susing Diffusion Tensor MRI (DT-MRI) and dense optical mapping data of the epicardium. This framework was then also applied to a clinical dataset derived from a hybrid XMR imaging and sparse electroanatomical mapping on a patient with heart failure. Next, the 3DMS model was also adapted to simulate the macroscopic structural behaviour of fibrosis near the scars. The simulation of an in silico VT stimulation study using the personalised adapted MS model was then performed, to quantify VT risk in terms of inducibility maps, re-entry patterns and exit point maps. A rule-based modelling approach for RF ablation lesions based on state of the art studies was proposed. Lastly, the in silico VT stimulation study was applied to in vivo personalised data of patients who underwent a clinical VT stimulation study. A validation of the in silico post-infarct VT prediction was performed against the clinically induced VT. Therole of spatial heterogeneity of the estimated patient’s cardiac tissue properties in the genesis of ischemic VT was learnt, along with their characteristics for entry/exit points, which are the potential candidates for RF ablation.

Diploma Thesis "Analysis of Czech dailies' content in relation to political parties during election campaign before municipal elections in Prague" presupposes that media and politics influence each other very strongly. In the theoretical part it first presents the media's role in society and describes the journalists' role evolution. Using the concept of mediatization it explains the media and political logic(s) inter-relation. In the next chapter it presents the historical development of political communication with regards to its ongoing transformation. After that it explains several concepts that are used when describing this process. Particularly it presents the concept of personalization and describes its two forms followed by definitions and critical evaluation of the concepts. In the empirical part it first presents the parties, dailies and municipal elections in the Czech Republic. Using the research method of quantitative content analysis it tries to find out the amount of attention/space that parties and candidates got in the newspapers during eleven weeks before the municipal elections in Prague in 2010. As a second step it tries to find out the level of personalization and its pre-defined forms. In the final part it presents the results and suggests possible extensions of the research.

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Cette recherche s'inscrit dans le domaine de la personnalisation d'Entrepôt de Données (ED) et concerne l'aide à l'exploitation d'un ED. Nous intéressons à l'assistance à apporter à un utilisateur lors d'une analyse en ligne, dans son utilisation de ressources d'exploitation existantes. Le domaine d'application concerné est la gestion hospitalière, dans le cadre de la nouvelle gouvernance, et en se limitant au périmètre du Programme de Médicalisation des Systèmes d'Information (PMSI). Cette recherche a été supportée par l'Assistance Publique des Hôpitaux de Marseille (APHM). L'approche retenue pour développer une telle assistance à l'utilisateur d'ED est sémantique et guidée par l'usage d'ontologies. Le système d'assistance mettant en oeuvre cette approche, nommé Ontologies-based Personalization System (OPS), s'appuie sur une Base de Connaissances (BC) exploitée par un moteur de personnalisation. La BC est composée des trois ontologies : de domaine, de l'ED et des ressources. Le moteur de personnalisation permet d'une part une recherche personnalisée de ressources d'exploitation de l'ED en s'appuyant sur le profil de l'utilisateur, et d'autre part pour une ressource particulière, une recommandation de ressources complémentaires selon trois stratégies possibles. Afin de valider nos propositions, un prototype du système OPS a été développé avec un moteur de personnalisation a été implémenté en Java et exploitant une base de connaissance constituée des trois ontologies en OWL interconnectées. Nous illustrons le fonctionnement de notre système sur trois scenarii d'expérimentation liés au PMSI et définis avec des experts métiers de l'APHM. / This research is situated in the domain of Data Warehouses (DW) personalization and concerns DW assistance. Specifically, we are interested in assisting a user during an online analysis processes to use existing operational resources. The application of this research concerns hospital management, for hospitals governance, and is limited to the scope of the Program of Medicalization of Information Systems (PMSI). This research was supported by the Public Hospitals of Marseille (APHM). Our proposal is a semantic approach based on ontologies. The support system implementing this approach, called Ontology-based Personalization System (OPS), is based on a knowledge base operated by a personalization engine. The knowledge base is composed of three ontologies: a domain ontology, an ontology of the DW structure, and an ontology of resources. The personalization engine allows firstly, a personalized search of resources of the DW based on users profile, and secondly for a particular resource, an expansion of the research by recommending new resources based on the context of the resource. To recommend new resources, we have proposed three possible strategies. To validate our proposal, a prototype of the OPS system was developed, a personalization engine has been implemented in Java. This engine exploit an OWL knowledge composed of three interconnected OWL ontologies. We illustrate three experimental scenarios related to PMSI and defined with APHM domain experts.

Artificial intelligence (AI) continues to gain traction and is increasingly reshaping the media and marketing communications field. While significant research has been conducted on the impact of AI in other fields, there is little empirical evidence on how AI is affecting the customer journey. The present study explored both organizations’ current use of AI tools and how customer perceptions about AI affect AI usage and adoption through the lens of diffusion of innovation theory. The research was conducted using mixed-method qualitative research. In-depth interviews and a case study content analysis were conducted to collect and analyze the data. The results suggest that consumer perceptions about AI impact levels of adoption when AI is recognized, but there appears to be cognitive dissonance regarding what constitutes AI and complicit acceptance of some of its benefits. Companies in different geographical locations have different levels of AI adoption along the diffusion of innovation stages.

A popularização de aplicativos e dispositivos capazes de produzir, exibir e editar conteúdos multimídia fez surgir a necessidade de se adaptar, modificar e customizar diferentes tipos de mídia a diferentes necessidades do usuário. Nesse contexto, a área de Personalização e Adaptação de Conteúdo busca desenvolver soluções que atendam a tais necessidades. Sistemas de personalização, em geral, necessitam conhecer os dados presentes na mídia, surgindo, assim, a necessidade de uma indexação do conteúdo presente na mídia. No caso de vídeo digital, os esforços para a indexação automática utilizam como passo inicial a segmentação de vídeos em unidades de informação menores, como tomadas e cenas. A segmentação em cenas, em especial, é um desafio para pesquisadores graças a enorme variedade entre os vídeos e a própria ausência de um consenso na definição de cena. Diversas técnicas diferentes para a segmentação em cenas são reportadas na literatura. Uma técnica, em particular, destaca-se pelo baixo custo computacional: a técnica baseada em coerências visual. Utilizando-se operações de histogramas, a técnica objetiva-se a comparar tomadas adjacentes em busca de similaridades que poderiam indicar a presença de uma cena. Para melhorar os resultados obtidos, autores de trabalhos com tal enfoque utilizam-se de outras características, capazes de medir a \"quantidade de movimento\" das cenas, como os vetores de movimento. Assim, este trabalho apresenta uma técnica de segmentação de vídeo digital em tomadas e em cenas através da coerência visual e do fluxo óptico. Apresenta-se, ainda, uma série de avaliações de eficácia e de desempenho da técnica ao segmentar em tomadas e em cenas uma base de vídeo do domínio filmes / The popularization of applications and devices capable of producing, displaying and editing multimedia content did increase the need to adapt, modify and customize different types of media for different user needs. In this context, the area of Personalization and Content Adaptation seeks to develop solutions that meet these needs. Personalization systems, in general, need to know the data present in the media, thus needing for a media indexing process. In the case of digital video, the efforts for automatic indexing usually involves, as an initial step, to segment videos into smaller information units, such as shots and scenes. The scene segmentation, in particular, is a challenge to researchers due to the huge variety among the videos and the very absence of a consensus on the scene definition. Several scenes segmentation techniques are reported in the literature. One technique in particular stands out for its low computational cost: those techniques based on visual coherence. By using histograms, the technique compares adjacent shots to find similar shots which may indicate the presence of a scene. To improve the results, some related works uses other features to evaluate the motion dynamics of the scenes using features such as motion vectors. In this sense, this work presents a digital video segmentation technique for shots and scenes, using visual coherence and optical flow as its features. It also presents a series of evaluation in terms of effectiveness and performance of the technique when segmenting scenes and shots of a custom video database of the film domain