Visual Targeted Advertisement System Based on User Profiling and Content Consumption for Mobile Broadcasting Television

Content personalisation is one of the main aims of the mobile media delivery business models, as a new way to improve the user’s experience. In broadcasting networks, the content is sent “one to many”, so a complete personalisation where the user may select any content is not possible. But using the mobile bidirectional return channel (e.g. UMTS connection) visual targeted advertising can be performed in a simple way: by off-line storing the advertisement for selectively replacing the normal broadcasted advertisement. In fact, these concepts provide powerful methods to increase the value of the service, mainly in mobile environments. In this article we present a novel intelligent content personalisation system for targeted advertising over mobile broadcasting networks and terminals, based on user profiling and clustering, as a new solution where the use of content personalisation represents the competitive advantage over traditional advertising

イノベーティブ融合サービスの導入と普及に関する研究

学位の種別:論文博士University of Tokyo(東京大学

Evaluation of unidirectional background push content download services for the delivery of television programs

Este trabajo de tesis presenta los servicios de descarga de contenido en modo push como un mecanismo eficiente para el envío de contenido de televisión pre-producido sobre redes de difusión. Hoy en día, los operadores de red dedican una cantidad considerable de recursos de red a la entrega en vivo de contenido televisivo, tanto sobre redes de difusión como sobre conexiones unidireccionales. Esta oferta de servicios responde únicamente a requisitos comerciales: disponer de los contenidos televisivos en cualquier momento y lugar. Sin embargo, desde un punto de vista estrictamente académico, el envío en vivo es únicamente un requerimiento para el contenido en vivo, no para contenidos que ya han sido producidos con anterioridad a su emisión. Más aún, la difusión es solo eficiente cuando el contenido es suficientemente popular. Los servicios bajo estudio en esta tesis utilizan capacidad residual en redes de difusión para enviar contenido pre-producido para que se almacene en los equipos de usuario. La propuesta se justifica únicamente por su eficiencia. Por un lado, genera valor de recursos de red que no se aprovecharían de otra manera. Por otro lado, realiza la entrega de contenidos pre-producidos y populares de la manera más eficiente: sobre servicios de descarga de contenidos en difusión. Los resultados incluyen modelos para la popularidad y la duración de contenidos, valiosos para cualquier trabajo de investigación basados en la entrega de contenidos televisivos. Además, la tesis evalúa la capacidad residual disponible en redes de difusión, por medio de estudios empíricos. Después, estos resultados son utilizados en simulaciones que evalúan las prestaciones de los servicios propuestos en escenarios diferentes y para aplicaciones diferentes. La evaluación demuestra que este tipo de servicios son un recurso muy útil para la entrega de contenido televisivo.This thesis dissertation presents background push Content Download Services as an efficient mechanism to deliver pre-produced television content through existing broadcast networks. Nowadays, network operators dedicate a considerable amount of network resources to live streaming live, through both broadcast and unicast connections. This service offering responds solely to commercial requirements: Content must be available anytime and anywhere. However, from a strictly academic point of view, live streaming is only a requirement for live content and not for pre-produced content. Moreover, broadcasting is only efficient when the content is sufficiently popular. The services under study in this thesis use residual capacity in broadcast networks to push popular, pre-produced content to storage capacity in customer premises equipment. The proposal responds only to efficiency requirements. On one hand, it creates value from network resources otherwise unused. On the other hand, it delivers popular pre-produced content in the most efficient way: through broadcast download services. The results include models for the popularity and the duration of television content, valuable for any research work dealing with file-based delivery of television content. Later, the thesis evaluates the residual capacity available in broadcast networks through empirical studies. These results are used in simulations to evaluate the performance of background push content download services in different scenarios and for different applications. The evaluation proves that this kind of services can become a great asset for the delivery of television contentFraile Gil, F. (2013). Evaluation of unidirectional background push content download services for the delivery of television programs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31656TESI

Predicción de Audiencias de Televisión basada en Sistemas Recomendadores

En este trabajo se presenta un método para la predicción de audiencias de televisión a partir de los perfiles de los telespectadores recibidos desde sus receptores de televisión digital. La predicción está basada en un recomendador de contenidos audiovisuales, aplicado sobre grupos de televidentes, que utiliza clasificaciones multidimensionales extraídas de la norma TV-Anytime. Se presentan dos aplicaciones ilustrativas, con el objetivo común de maximizar la calificación en dos contextos distintos: un primer algoritmo para configurar la parrilla de programación semanal de una estación de televisión, y otro que decide en tiempo real entre un conjunto de contenidos cuál de ellos debe ser transmitido en un momento determinado por una estación de televisión para maximizar su audiencia inmediata

Utilizando Sistemas Recomendadores para Predecir Ratings en TV

En este trabajo se presenta un método que, utilizando sistemas recomendadores, predice ratings de TV a partir de los perfiles de los telespectadores recibidos desde sus receptores de televisión digital. La predicción está basada en un recomendador de contenidos audiovisuales, aplicado sobre grupos de televidentes, que utiliza clasificaciones multidimensionales extraídas de la norma TV-Anytime. Se presentan dos aplicaciones ilustrativas, con el objetivo común de maximizar la calificación en dos contextos distintos: un primer algoritmo para configurar la parrilla de programación semanal de una estación de televisión, y otro que decide en tiempo real entre un conjunto de contenidos cuál de ellos debe ser transmitido en un momento determinado por una estación de televisión para maximizar su audiencia inmediata

Online users' behaviours and behavioural intentions with reference to live streaming : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University, Albany, New Zealand. EMBARGOED until 26 March 2023.

Embargoed until 26 March 2023Live streaming, as a new medium, allows users to participate in real-time interaction. It has attracted a large number of online users, and become a new social commerce venue and lucrative business, especially in China where the live streaming industry is growing explosively and is the largest in the world. This thesis aims to comprehensively investigate users’ behaviours and behavioural intentions in live streaming through both qualitative and quantitative approaches using the Chinese live streaming as an example. This thesis contains four studies to investigate from both streamers’ and viewers’ aspects. Firstly, we conducted two qualitative studies to investigate users’ online behaviours in the social commerce practice in live streaming by exploring how streamers attract viewers (Chapter 2) and encourage gifting (Chapter 3). Novel multiple triangulation was used, including data source triangulation and methodological triangulation. Through multiple triangulation, three behaviours for viewer attraction and four behaviours for gifting encouragement were identified. These two chapters help to comprehensively understand streamers’ online behaviours in this new form of social commerce. Next, we conducted two quantitative studies to explore why viewers continue to watch streams (Chapters 4 and 5). Based on expectation-confirmation theory (ECT), in Chapter 4, we modified the post-acceptance model of information system continuance and re-defined the constructs in a structural equation model of predictors of continuance intention of watching live streams. Chapter 4 successfully connects intention and continuance intention of watching, and integrates disparate understandings of viewers’ watching behaviours. To solve the deficiencies identified in current ECT-based models and further increase the explanation of variance in continuance intention of watching, in Chapter 5, we proposed a value-based continuance intention model (V-ECM), which theoretically extends ECT-based studies by including a process of overall practical assessment between users’ perceived benefits and perceived sacrifices. V-ECM appears to be a better model for explaining users’ continuance intention in the stream-watching context. Also, V-ECM could be used broadly in online and/or technology-related fields. Overall, this thesis comprehensively investigates both streamers’ and viewers’ behaviours and behavioural intentions in live streaming. Insights from this thesis can improve the design, functions and marketing within live streaming platforms. Also, this thesis provides strong foundations for further online behaviour studies, for example, stream-watching addiction

Towards a Video Consumer Leaning Spectrum: A Medium-Centric Approach

Purpose: As TV and digital video converge, there is a need to compare advertising effectiveness, advertising receptivity, and video consumption drivers in this new context. Considering the emerging viewing practices and underlying theories, this study examines the feasibility of the traditional notion of differentiating between lean-back (LB) and lean-forward (LF) media, and proposes a revised approach of addressing video consumption processes and associated advertising effectiveness implications. Methodology: An extensive, systematic literature review examines a total of 715 sources regarding current lean-back/lean-forward media research and alternative approaches as by (1) basic terminologies, (2) limitations of lean-back/lean-forward situations, (3) advertising effectiveness implications, (4) video-specific approaches. Findings/Contribution: Key differences between lean-back and lean-forward video consumption are presented. A conceptual integration of video ad receptivity/effectiveness drivers is proposed to guide future media and marketing research and practice. Video consumption today is no longer lean-back or lean-forward, but a “leaning spectrum” with two dimensions: leaning direction and leaning degree. Designing video content today requires focusing on consumption drivers and platform synergies for owning the “leaning spectrum”

Understanding motivations to use online streaming services : integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT)

Purpose: The outbreak of the Coronavirus (COVID-19) pandemic and its preventative social distancing measures have led to a dramatic increase in subscriptions to paid streaming services. Online users are increasingly accessing live broadcasts as well as recorded video content and digital music services through Internet and mobile devices. In this context, this study explores the individuals’ uses and gratifications from online streaming technologies during COVID-19. Design/Methodology/Approach: This research has adapted key measures from the ‘Technology Acceptance Model’ (TAM) and from the ‘Uses and Gratifications Theory’ (UGT) to better understand the individuals’ intentions to use online streaming technologies. A structural equations partial least squares’ (SEM-PLS 3) confirmatory composite approach was used to analyze the gathered data. Findings: The individuals’ perceived usefulness and ease of use of online streaming services were significant antecedents of their intentions to use the mentioned technologies. Moreover, this study suggests that the research participants sought emotional gratifications from online streaming technologies, as they allowed them to distract themselves into a better mood, and to relax in their leisure time. Evidently, they were using them to satisfy their needs for information and entertainment. Research implications: This study contributes to the academic literature by generating new knowledge about the individuals´ perceptions, motivations, and intentions to use online streaming technologies to watch recorded movies, series, and live broadcasts. Practical implications: The findings imply that there is scope for the providers of online streaming services to improve their customer-centric marketing by refining the quality and content of their recorded programs, and through regular interactions with subscribers and personalized recommender systems. Originality/Value: This study integrates the TAM and UGT frameworks to better understand the effects of the users’ perceptions, ritualized and instrumental motivations on their intentions to continue watching movies, series and broadcasts through online streaming technologies, during COVID-19.peer-reviewe

Entrega de conteúdos multimédia em over-the-top: caso de estudo das gravações automáticas

Doutoramento em Engenharia EletrotécnicaOver-The-Top (OTT) multimedia delivery is a very appealing approach for providing ubiquitous, exible, and globally accessible services capable of low-cost and unrestrained device targeting. In spite of its appeal, the underlying delivery architecture must be carefully planned and optimized to maintain a high Qualityof- Experience (QoE) and rational resource usage, especially when migrating from services running on managed networks with established quality guarantees. To address the lack of holistic research works on OTT multimedia delivery systems, this Thesis focuses on an end-to-end optimization challenge, considering a migration use-case of a popular Catch-up TV service from managed IP Television (IPTV) networks to OTT. A global study is conducted on the importance of Catch-up TV and its impact in today's society, demonstrating the growing popularity of this time-shift service, its relevance in the multimedia landscape, and tness as an OTT migration use-case. Catch-up TV consumption logs are obtained from a Pay-TV operator's live production IPTV service containing over 1 million subscribers to characterize demand and extract insights from service utilization at a scale and scope not yet addressed in the literature. This characterization is used to build demand forecasting models relying on machine learning techniques to enable static and dynamic optimization of OTT multimedia delivery solutions, which are able to produce accurate bandwidth and storage requirements' forecasts, and may be used to achieve considerable power and cost savings whilst maintaining a high QoE. A novel caching algorithm, Most Popularly Used (MPU), is proposed, implemented, and shown to outperform established caching algorithms in both simulation and experimental scenarios. The need for accurate QoE measurements in OTT scenarios supporting HTTP Adaptive Streaming (HAS) motivates the creation of a new QoE model capable of taking into account the impact of key HAS aspects. By addressing the complete content delivery pipeline in the envisioned content-aware OTT Content Delivery Network (CDN), this Thesis demonstrates that signi cant improvements are possible in next-generation multimedia delivery solutions.A entrega de conteúdos multimédia em Over-The-Top (OTT) e uma proposta atractiva para fornecer um serviço flexível e globalmente acessível, capaz de alcançar qualquer dispositivo, com uma promessa de baixos custos. Apesar das suas vantagens, e necessario um planeamento arquitectural detalhado e optimizado para manter níveis elevados de Qualidade de Experiência (QoE), em particular aquando da migração dos serviços suportados em redes geridas com garantias de qualidade pré-estabelecidas. Para colmatar a falta de trabalhos de investigação na área de sistemas de entrega de conteúdos multimédia em OTT, esta Tese foca-se na optimização destas soluções como um todo, partindo do caso de uso de migração de um serviço popular de Gravações Automáticas suportado em redes de Televisão sobre IP (IPTV) geridas, para um cenário de entrega em OTT. Um estudo global para aferir a importância das Gravações Automáticas revela a sua relevância no panorama de serviços multimédia e a sua adequação enquanto caso de uso de migração para cenários OTT. São obtidos registos de consumos de um serviço de produção de Gravações Automáticas, representando mais de 1 milhão de assinantes, para caracterizar e extrair informação de consumos numa escala e âmbito não contemplados ate a data na literatura. Esta caracterização e utilizada para construir modelos de previsão de carga, tirando partido de sistemas de machine learning, que permitem optimizações estáticas e dinâmicas dos sistemas de entrega de conteúdos em OTT através de previsões das necessidades de largura de banda e armazenamento, potenciando ganhos significativos em consumo energético e custos. Um novo mecanismo de caching, Most Popularly Used (MPU), demonstra um desempenho superior as soluções de referencia, quer em cenários de simulação quer experimentais. A necessidade de medição exacta da QoE em streaming adaptativo HTTP motiva a criaçao de um modelo capaz de endereçar aspectos específicos destas tecnologias adaptativas. Ao endereçar a cadeia completa de entrega através de uma arquitectura consciente dos seus conteúdos, esta Tese demonstra que são possíveis melhorias de desempenho muito significativas nas redes de entregas de conteúdos em OTT de próxima geração