Personalized Recommendations of Upcoming Sport Events

Recommender systems have emerged as essential tools for enhancing user engagement and content discovery in various domains, including the sports industry. In the context of sports viewing, personalized recommendations have become increasingly significant, enabling users to easily connect with their favorite sports teams, explore new content, and broaden their viewing preferences. Collaborative filtering (CF) stands out as a popular recommendation algorithm that analyzes the similarities and patterns in user-item interactions. By examining the behavior and preferences of a group of users, CF identifies similar users and recommends items that have been positively received by those with similar tastes. Applying CF to sports recommendations presents an opportunity to introduce users to new sports events enjoyed by their peers. However, recommending upcoming live sports events introduces unique challenges, such as limited availability and the need to strike a balance between catering to users' favorite sports and introducing them to new content. This master thesis aims to address these challenges through the development of a personalized recommendation system for upcoming sports events using CF. The system will analyze user viewing history to provide tailored recommendations that facilitate content discovery and enable users to easily locate their preferred sports events. The research objectives include identifying the most suitable collaborative filtering model for sports content recommendation, investigating the factors that influence sports fans' preferences for specific types of live sports events, and evaluating the effectiveness of personalized recommendations compared to non-personalized approaches. The proposed system is implemented and A/B tested on TV 2 Play, one of Norway's largest digital streaming platforms, with the ultimate goal of enhancing user experience and engagement by delivering personalized and relevant recommendations for sports content. This research contributes to the field by proposing a novel collaborative filtering recommender for sports based on user viewing sessions, exploring effective strategies for recommending upcoming live sports events, and assessing the system's performance in terms of accuracy and user satisfaction.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Erfassung der Effektivität von Sportsponsoring als Marketingkommunikationsinstrument auf der impliziten und expliziten Verarbeitungsebene von Konsumenten als Handlungsgrundlage für operative und strategische Managemententscheidungen

In den letzten drei Dekaden hat sich das Sponsoring im Allgemeinen und das Sportsponsoring im Besonderen als eine immer wichtigere und verstärkt verbindende Marketingkommunikationsplattform etablieren können. Im Kern versucht Sponsoring dabei, einen assoziativen Transfer zwischen der Sponsormarke und dem Sponsorobjekt (Event, Team, Athlet etc.) zu schaffen, welcher von dem Zuschauer bzw. Fan wertgeschätzt wird, um darüber die Markenwahrnehmung und das Markenverhalten zu beeinflussen. Aus moderner Kommunikationsperspektive, wie sie bei Sharp (2010) eingehend erörtert wird, sind weitere elementare Vorteile des Sponsoring, neben dem persönlichen Erreichen der Konsumenten, a) eine kontinuierliche und aufmerksamkeitsstarke Präsenz sowie b) das Auffrischen und Stärken von relevanten Assoziationen im menschlichen Gedächtnis zu ermöglichen. Cornwell et al. (2005) identifizieren in diesem Zusammenhang den folgenden Bedarf bei der Sponsoringforschung: „Implicit memory also plays a major role in the processing of sponsorship information. As such, greater consideration in future research must be given to investigating implicit memory for sponsorship information, rather than just using studies involving sponsor recall and recognition tasks tapping explicit memory.” (Cornwell et al. 2005, p. 29). Auf akademischer und praktischer Ebene ist festzustellen, dass lediglich in wenigen Sportsponsoring-Studien implizite Erhebungstechniken eingesetzt wurden, wie es auch generell im Marketing zu beobachten ist, obwohl dies Cornwell et al. (2005) in deren viel beachteten und zitierten Artikel als zukünftige Notwendigkeit klar identifiziert und gezielt hervorgehoben haben. Den Ausgangspunkt zum systematischen Verständnis der Sponsoringwirksamkeit bildet die assoziative Netzwerktheorie. Jeder Marketingkontakt wie das Wahrnehmen des Trikotsponsors oder der Post eines Athleten in den Sozialen Medien über den neuen Ausrüster, ob nun persönlich bzw. direkt oder nicht-persönlich bzw. indirekt erfahren, löst einen assoziativen Lernprozess aus, der neue Assoziationen im impliziten Gedächtnis speichert, bestehende Assoziationen verstärkt oder überschreibt und darüber am Ende den Marketingerfolg wie Markengefallen oder Markenkauf beeinflusst. Vor den skizzierten Hintergründen und den identifizierten Forschungslücken auf praktischer, theoretischer, methodischer und empirischer Ebene ergibt sich ableitend die folgende Motivation für die Durchführung einer systematischen Forschungsreihe: Schaffung eines erkenntnisleitenden Beitrages zur Wirksamkeit von horizontal und vertikal ausgerichteten Sportsponsoringaktivitäten auf impliziter und expliziter Ebene der Markeninformationsverarbeitung. Die einzelnen Studien der Forschungsreihe, welche insgesamt sechs aufeinander aufbauende Arbeiten umfasst, fallen in den Bereich einer verhaltenswissenschaftlichen Fundierung des Marketing im Allgemeinen und der Marketingforschung im Besonderen. Ziel der Forschungsreihe ist die Initiierung eines wissenschaftlich fundierten Erkenntnisfortschritts bei gleichzeitig hoher Praxisorientierung. Das Verständnis sowie der Nachweis, welche substanzielle Wirksamkeit eine Sportsponsoringaktivität hinterlässt, insbesondere bezüglich der markenwertspezifischen Assoziationen im Gedächtnis der Konsumenten, die in ihrer Gesamtheit das Bild einer Marke, präziser formuliert das Markenwissen determinieren und entsprechend die Wahrnehmung als auch das Verhalten gegenüber einer Marke beeinflussen, ist für das Marketingmanagement einer Sponsormarke von erfolgskritischer Relevanz. Die durchgeführten Forschungsstudien zielten darauf ab, eine inhaltliche und methodische Weiterentwicklung der Sportsponsoringforschung aus Perspektive der Wissenschaft und Praxis systematisch umzusetzen. Mittels einer kombinierten Erhebung und Analyse impliziter und expliziter Markenassoziationen sowie zusätzlicher markenwertrelevanter Engagementmaße wie Markenempfindung, -weiterempfehlung und -präferenz – wie im Rahmen der vorliegenden Forschungsreihe erfolgreich konzipiert, eingesetzt, überprüft und sukzessive weiterentwickelt wurde – lässt sich die Sponsoringwirksamkeit in einer kompakten und gleichzeitig ganzheitlichen Art und Weise sowohl wissenschaftlich fundiert als auch praxistauglich evaluieren. Insbesondere die zielorientierte und multidimensionale Erfassung von impliziten Markenassoziationen, wie von Cornwell et al. (2005) als kritisches Forschungsdefizit identifiziert, erwies sich als leistungsstark und wertvoll. Aus Perspektive des Marketingmanagement zeigt die vorliegende empirische Forschungsreihe ebenfalls die kritische Notwendigkeit des kombinierten Einsatzes aus impliziten und expliziten Erhebungsinstrumenten, um ein ganzheitliches Verständnis entwickeln zu können, wie Konsumenten die Marke und damit einhergehend die Markenkommunikation wahrnehmen und verarbeiten. Des Weiteren scheint es aus Perspektive des Marketingmanagement angebracht, die Wirksamkeit einer Sponsoringaktivität im Vorfeld anhand des Assoziationsfits zwischen Sponsorobjekt und Sponsormarke analytisch abzuschätzen. Nur wenn am Ende das Sponsorobjekt im Vergleich zur Sponsormarke bei den Assoziationen klar besser abschneidet, die für die Sponsormarke mit Blick auf eine positive Konsumentenreaktion essentiell sind, scheint ein Sponsoringinvestment zweckmäßig, da dann ein positiver Assoziationstransfer vom Sponsorobjekt auf die Sponsormarke wahrscheinlich ist, welcher einen nachhaltigen Ausbau und eine substanzielle Stärkung des Markenwissens ermöglicht

A study on Analysis and Utilization of Crowd-sourced Spatio-temporal Contexts from Social Media

兵庫県立大学大学院201

CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

Service Platform for Converged Interactive Broadband Broadcast and Cellular Wireless

A converged broadcast and telecommunication service platform is presented that is able to create, deliver, and manage interactive, multimedia content and services for consumption on three different terminal types. The motivations of service providers for designing converged interactive multimedia services, which are crafted for their individual requirements, are investigated. The overall design of the system is presented with particular emphasis placed on the operational features of each of the sub-systems, the flows of media and metadata through the sub-systems and the formats and protocols required for inter-communication between them. The key features of tools required for creating converged interactive multimedia content for a range of different end-user terminal types are examined. Finally possible enhancements to this system are discussed. This study is of particular interest to those organizations currently conducting trials and commercial launches of DVB-H services because it provides them with an insight of the various additional functions required in the service provisioning platforms to provide fully interactive services to a range of different mobile terminal types

Hybrid human-AI driven open personalized education

Attaining those skills that match labor market demand is getting increasingly complicated as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Furthermore, people's interests in gaining knowledge pertaining to their personal life (e.g., hobbies and life-hacks) are also increasing dramatically in recent decades. In this situation, anticipating and addressing the learning needs are fundamental challenges to twenty-first century education. The need for such technologies has escalated due to the COVID-19 pandemic, where online education became a key player in all types of training programs. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open/free educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. Therefore, this thesis aims to contribute to the literature about the utilization of (open and free-online) educational resources toward goal-driven personalized informal learning, by developing a novel Human-AI based system, called eDoer. In this thesis, we discuss all the new knowledge that was created in order to complete the system development, which includes 1) prototype development and qualitative user validation, 2) decomposing the preliminary requirements into meaningful components, 3) implementation and validation of each component, and 4) a final requirement analysis followed by combining the implemented components in order develop and validate the planned system (eDoer). All in all, our proposed system 1) derives the skill requirements for a wide range of occupations (as skills and jobs are typical goals in informal learning) through an analysis of online job vacancy announcements, 2) decomposes skills into learning topics, 3) collects a variety of open/free online educational resources that address those topics, 4) checks the quality of those resources and topic relevance using our developed intelligent prediction models, 5) helps learners to set their learning goals, 6) recommends personalized learning pathways and learning content based on individual learning goals, and 7) provides assessment services for learners to monitor their progress towards their desired learning objectives. Accordingly, we created a learning dashboard focusing on three Data Science related jobs and conducted an initial validation of eDoer through a randomized experiment. Controlling for the effects of prior knowledge as assessed by the pretest, the randomized experiment provided tentative support for the hypothesis that learners who engaged with personal eDoer recommendations attain higher scores on the posttest than those who did not. The hypothesis that learners who received personalized content in terms of format, length, level of detail, and content type, would achieve higher scores than those receiving non-personalized content was not supported as a statistically significant result

Dynamic learning and refinement of preferences through keywords

The main goal in this work is to learn user preferences in situations where the objects to be treated are formed only by textual information and we continuously have information of selections made by the user. This work has been divided in two major parts: the first one including the algorithms and techniques to rank a set of alternatives, and the second one including the techniques to maintain the profile up to date. Regarding the first part, the goal is to evaluate an object of type text, i.e. given the user preferences to assign the degree of potential interest on that object. This will allow us to evaluate the set of alternatives and to sort them according to the user preferences. Concerning the second part, the main goal is to design a method to update the user profile, given the user selection from a set of alternatives in the first part. This method will allow to adapt a user profile in an unsupervised and dynamic way. To achieve these objectives it is necessary to fulfil the tasks discussed in this document and named below in the document organization