313 research outputs found

    Context-aware LDA: Balancing Relevance and Diversity in TV Content Recommenders

    Get PDF
    In the vast and expanding ocean of digital content, users are hardly satisïŹed with recommended programs solely based on static user patterns and common statistics. Therefore, there is growing interest in recommendation approaches that aim to provide a certain level of diversity, besides precision and ranking. Context-awareness, which is an eïŹ€ective way to express dynamics and adaptivity, is widely used in recom-mender systems to set a proper balance between ranking and diversity. In light of these observations, we introduce a recommender with a context-aware probabilistic graphi-cal model and apply it to a campus-wide TV content de-livery system named “Vision”. Within this recommender, selection criteria of candidate ïŹelds and contextual factors are designed and users’ dependencies on their personal pref-erence or the aforementioned contextual inïŹ‚uences can be distinguished. Most importantly, as to the role of balanc-ing relevance and diversity, ïŹnal experiment results prove that context-aware LDA can evidently outperform other al-gorithms on both metrics. Thus this scalable model can be ïŹ‚exibly used for diïŹ€erent recommendation purposes

    Context aware advertising

    Get PDF
    IP Television (IPTV) has created a new arena for digital advertising that has not been explored to its full potential yet. IPTV allows users to retrieve on demand content and recommended content; however, very limited research has been applied in the domain of advertising in IPTV systems. The diversity of the field led to a lot of mature efforts in the fields of content recommendation and mobile advertising. The introduction of IPTV and smart devices led to the ability to gather more context information that was not subject of study before. This research attempts at studying the different contextual parameters, how to enrich the advertising context to tailor better ads for users, devising a recommendation engine that utilizes the new context, building a prototype to prove the viability of the system and evaluating it on different quality of service and quality of experience measures. To tackle this problem, a review of the state of the art in the field of context-aware advertising as well as the related field of context-aware multimedia have been studied. The intent was to come up with the most relevant contextual parameters that can possibly yield a higher percentage precision for recommending advertisements to users. Subsequently, a prototype application was also developed to validate the feasibility and viability of the approach. The prototype gathers contextual information related to the number of viewers, their age, genders, viewing angles as well as their emotions. The gathered context is then dispatched to a web service which generates advertisement recommendations and sends them back to the user. A scheduler was also implemented to identify the most suitable time to push advertisements to users based on their attention span. To achieve our contributions, a corpus of 421 ads was gathered and processed for streaming. The advertisements were displayed in reality during the holy month of Ramadan, 2016. A data gathering application was developed where sample users were presented with 10 random ads and asked to rate and evaluate the advertisements according to a predetermined criteria. The gathered data was used for training the recommendation engine and computing the latent context-item preferences. This also served to identify the performance of a system that randomly sends advertisements to users. The resulting performance is used as a benchmark to compare our results against. When it comes to the recommendation engine itself, several implementation options were considered that pertain to the methodology to create a vector representation of an advertisement as well as the metric to use to measure the similarity between two advertisement vectors. The goal is to find a representation of advertisements that circumvents the cold start problem and the best similarity measure to use with the different vectorization techniques. A set of experiments have been designed and executed to identify the right vectorization methodology and similarity measure to apply in this problem domain. To evaluate the overall performance of the system, several experiments were designed and executed that cover different quality aspects of the system such as quality of service, quality of experience and quality of context. All three aspects have been measured and our results show that our recommendation engine exhibits a significant improvement over other mechanisms of pushing ads to users that are employed in currently existing systems. The other mechanisms placed in comparison are the random ad generation and targeted ad generation. Targeted ads mechanism relies on demographic information of the viewer with disregard to his/her historical consumption. Our system showed a precision percentage of 69.70% which means that roughly 7 out of 10 recommended ads are actually liked and viewed to the end by the viewer. The practice of randomly generating ads yields a result of 41.11% precision which means that only 4 out of 10 recommended ads are actually liked by viewers. The targeted ads system resulted in 51.39% precision. Our results show that a significant improvement can be introduced when employing context within a recommendation engine. When introducing emotion context, our results show a significant improvement in case the userñ€ℱs emotion is happiness; however, it showed a degradation of performance when the userñ€ℱs emotion is sadness. When considering all emotions, the overall results did not show a significant improvement. It is worth noting though that ads recommended based on detected emotions using our systems proved to always be relevant to the user\u27s current mood

    Converged Digital TV Services: The Role of Middleware and Future Directions of Interactive Television

    Get PDF
    The migration from analog to digital of the broadcasting technologies, already well consolidated for satellite systems, is becoming a reality also for terrestrial transmission. Digital Terrestrial Television (DTT) is also evolving to offer interactive services and a degree of flexibility which can be exploited to offer tailored applications to users which include, for instance interactivity, different levels of personalization, and innovative location-based, as well as context-aware, services. A clear example of this trend is given by the rising success of the Internet Protocol Television (IPTV) which allows for a degree of flexibility on offered services unknown to the traditional broadcasting systems. In this framework, several satellite operators are starting to launch IPTV services using direct satellite links, as well as some terrestrial internet service providers are offering digital TV channels embedded in the IP streaming over XDSL. Furthermore, IPTV services are likely to be broadcast also wirelessly, exploiting advanced broadband access technologies such asWiMAX, LTE, or LTEA. Last, but not least, TV and broadcast services for mobile users have also been deployed in many countries using DVBH and will be soon available on an even broader scale thanks to its satellite counterpart, DVB-SH. In the near future, a set of different technologies able to offer personalized and customized services to different classes of users are expected in the area of wireless broadcasting and convergence of technologies is auspicious. This concept entails different levels of convergence, namely, at terminal level (one device fits all), at service level (convergence of traditional fixed, mobile, and broadcast services), and at transport and network level with a common and standardized set of protocols and at access layer thanks to the harmonic coexistence of different radio technologies. This special issue aims to capture the state-of-the-art research work concerning the integration of DTT/Satellite/IPTV systems for the broadcasting of multimedia and interactive services

    Individualisation avancée des services IPTV

    Get PDF
    Le monde de la TV est en cours de transformation de la tĂ©lĂ©vision analogique Ă  la tĂ©lĂ©vision numĂ©rique, qui est capable de diffuser du contenu de haute qualitĂ©, offrir aux consommateurs davantage de choix, et rendre l'expĂ©rience de visualisation plus interactive. IPTV (Internet Protocol TV) prĂ©sente une rĂ©volution dans la tĂ©lĂ©vision numĂ©rique dans lequel les services de tĂ©lĂ©vision numĂ©rique sont fournis aux utilisateurs en utilisant le protocole Internet (IP) au dessus d une connexion haut dĂ©bit. Les progrĂšs de la technologie IPTV permettra donc un nouveau modĂšle de fourniture de services. Les fonctions offertes aux utilisateurs leur permettent de plus en plus d autonomie et de plus en plus de choix. Il en est notamment ainsi de services de type nTS (pour network Time Shifting en anglais) qui permettent Ă  un utilisateur de visionner un programme de tĂ©lĂ©vision en dĂ©calage par rapport Ă  sa programmation de diffusion, ou encore des services de type nPVR (pour network Personal Video Recorder en anglais) qui permettent d enregistrer au niveau du rĂ©seau un contenu numĂ©rique pour un utilisateur. D'autre part, l'architecture IMS proposĂ©e dans NGN fournit une architecture commune pour les services IPTV. MalgrĂ© les progrĂšs rapides de la technologie de tĂ©lĂ©vision interactive (comprenant notamment les technologies IPTV et NGN), la personnalisation de services IPTV en est encore Ă  ses dĂ©buts. De nos jours, la personnalisation des services IPTV se limite principalement Ă  la recommandation de contenus et Ă  la publicitĂ© ciblĂ©e. Ces services ne sont donc pas complĂštement centrĂ©s sur l utilisateur, alors que choisir manuellement les canaux de diffusion et les publicitĂ©s dĂ©sirĂ©es peut reprĂ©senter une gĂȘne pour l utilisateur. L adaptation des contenus numĂ©riques en fonction de la capacitĂ© des rĂ©seaux et des dispositifs utilisĂ©s n est pas encore prise en compte dans les implĂ©mentations actuelles. Avec le dĂ©veloppement des technologies numĂ©riques, les utilisateurs sont amenĂ©s Ă  regarder la tĂ©lĂ©vision non seulement sur des postes de tĂ©lĂ©vision, mais Ă©galement sur des smart phones, des tablettes digitales, ou encore des PCs. En consĂ©quence, personnaliser les contenus IPTV en fonction de l appareil utilisĂ© pour regarder la tĂ©lĂ©vision, en fonction des capacitĂ©s du rĂ©seau et du contexte de l utilisateur reprĂ©sente un dĂ©fi important. Cette thĂšse prĂ©sente des solutions visant Ă  amĂ©liorer la personnalisation de services IPTV Ă  partir de trois aspects: 1) Nouvelle identification et authentification pour services IPTV. 2) Nouvelle architecture IPTV intĂ©grĂ©e et comportant un systĂšme de sensibilitĂ© au contexte pour le service de personnalisation. 3) Nouveau service de recommandation de contenu en fonction des prĂ©fĂ©rences de l utilisateur et aussi des informations contextesInternet Protocol TV (IPTV) delivers television content to users over IP-based network. Different from the traditional TV services, IPTV platforms provide users with large amount of multimedia contents with interactive and personalized services, including the targeted advertisement, on-demand content, personal video recorder, and so on. IPTV is promising since it allows to satisfy users experience and presents advanced entertainment services. On the other hand, the Next Generation Network (NGN) approach in allowing services convergence (through for instance coupling IPTV with the IP Multimedia Subsystem (IMS) architecture or NGN Non-IMS architecture) enhances users experience and allows for more services personalization. Although the rapid advancement in interactive TV technology (including IPTV and NGN technologies), services personalization is still in its infancy, lacking the real distinguish of each user in a unique manner, the consideration of the context of the user (who is this user, what is his preferences, his regional area, location, ..) and his environment (characteristics of the users devices screen types, size, supported resolution, and networks available network types to be used by the user, available bandwidth, .. ) as well as the context of the service itself (content type and description, available format HD/SD , available language, ..) in order to provide the adequate personalized content for each user. This advanced IPTV services allows services providers to promote new services and open new business opportunities and allows network operators to make better utilization of network resources through adapting the delivered content according to the available bandwidth and to better meet the QoE (Quality of Experience) of clients. This thesis focuses on enhanced personalization for IPTV services following a user-centric context-aware approach through providing solutions for: i) Users identification during IPTV service access through a unique and fine-grained manner (different from the identification of the subscription which is the usual current case) based on employing a personal identifier for each user which is a part of the user context information. ii) Context-Aware IPTV service through proposing a context-aware system on top of the IPTV architecture for gathering in a dynamic and real-time manner the different context information related to the user, devices, network and service. The context information is gathered throughout the whole IPTV delivery chain considering the user domain, network provider domain, and service/content provider domain. The proposed context-aware system allows monitoring user s environment (devices and networks status), interpreting user s requirements and making the user s interaction with the TV system dynamic and transparent. iii) Personalized recommendation and selection of IPTV content based on the different context information gathered and the personalization decision taken by the context-aware system (different from the current recommendation approach mainly based on matching content to users preferences) which in turn highly improves the users Quality of Experience (QoE) and enriching the offers of IPTV servicesEVRY-INT (912282302) / SudocSudocFranceF

    Dataretrieving for varied in different Composition Databases using Content aggregation

    Get PDF
    Keeping in mind with a variety of content choices, consumers are exhibiting diverse preferences for content; their preferences often depend on the context in which they consume content as well as various exogenous events. To satisfy the consumersïżœ demand for such diverse content, multimedia content aggregators (CAs) haveemerged which gather content from numerous multimedia sources. A key challenge for such systems is to accurately predict whattype of content each of its consumers prefers in a certain context,and adapt these predictions to the evolving consumers preferences, contexts, and content characteristics This paper addressesgenerate text based file data sets, such as word, text files, image file data sets, and video file data sets, It also extract data from multiple databases, evaluate user preference based query, reduce time complexity by clustering data, and increase fetching speed by using query classification

    Context-aware LDA: Balancing Relevance and Diversity in TV Content Recommenders

    Get PDF
    In the vast and expanding ocean of digital content, users are hardly satisïŹed with recommended programs solely based on static user patterns and common statistics. Therefore, there is growing interest in recommendation approaches that aim to provide a certain level of diversity, besides precision and ranking. Context-awareness, which is an eïŹ€ective way to express dynamics and adaptivity, is widely used in recom-mender systems to set a proper balance between ranking and diversity. In light of these observations, we introduce a recommender with a context-aware probabilistic graphi-cal model and apply it to a campus-wide TV content de-livery system named “Vision”. Within this recommender, selection criteria of candidate ïŹelds and contextual factors are designed and users’ dependencies on their personal pref-erence or the aforementioned contextual inïŹ‚uences can be distinguished. Most importantly, as to the role of balanc-ing relevance and diversity, ïŹnal experiment results prove that context-aware LDA can evidently outperform other al-gorithms on both metrics. Thus this scalable model can be ïŹ‚exibly used for diïŹ€erent recommendation purposes

    FamTV : an architecture for presence-aware personalized television

    Get PDF
    Since the advent of the digital era, the traditional TV scenario has rapidly evolved towards an ecosystem comprised of a myriad of services, applications, channels, and contents. As a direct consequence, the amount of available information and configuration options targeted at today's end consumers have become unmanageable. Thus, personalization and usability emerge as indispensable elements to improve our content-overloaded digital homes. With these requirements in mind, we present a way to combine content adaptation paradigms together with presence detection in order to allow a seamless and personalized entertainment experience when watching TV.This work has been partially supported by the Community of Madrid (CAM), Spain under the contract number S2009/TIC-1650.Publicad

    HUC-HISF: A Hybrid Intelligent Security Framework for Human-centric Ubiquitous Computing

    Get PDF
    戶ćșŠ:新 ; 栱摊ç•Șć·:äč™2336ć· ; ć­ŠäœăźçšźéĄž:ćšćŁ«(äșș間科歩) ; 授䞎ćčŽæœˆæ—„:2012/1/18 ; æ—©ć€§ć­Šäœèš˜ç•Șć·:新584

    Personalized object-based audio for hearing impaired TV viewers

    Get PDF
    Age demographics have led to an increase in the proportion of the population suffering from some form of hearing loss. The introduction of object-based audio to television broadcast has the potential to improve the viewing experience for millions of hearing impaired people. Personalization of object-based audio can assist in overcoming difficulties in understanding speech and understanding the narrative of broadcast media. The research presented here documents a Multi-Dimensional Audio (MDA) implementation of object-based clean audio to present independent object streams based on object category elicitation. Evaluations were carried out with hearing impaired people and participants were able to personalize audio levels independently for four object-categories using an on-screen menu: speech, music, background effects and foreground effects related to on-screen events. Results show considerable preference variation across subjects but indicate that expanding object-category personalization beyond a binary speech/non-speech categorization can substantially improve the viewing experience for some hearing impaired people
    • 

    corecore