Video Recommendations Based on Visual Features Extracted with Deep Learning

Postponed access: the file will be accessible after 2022-06-01When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list, known as Cold-start problem. This thesis investigates recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. The proposed technique has been evaluated in both offline and online evaluations using a large dataset of movies. The online evaluation has been carried out in a evaluation framework developed for this thesis. Results from the offline and online evaluation (N=150) show that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features. The results also point to subtitles as a high-quality future source of automatically extracted features. The visual feature dataset, named DeepCineProp13K and the subtitle dataset, CineSub3K, as well as the proposed evaluation framework are all made openly available online in a designated Github repository.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

The Right to be an Exception to Predictions: a Moral Defense of Diversity in Recommendation Systems

Recommendation systems (RSs) predict what the user likes and recommend it to them. While at the onset of RSs, the latter was designed to maximize the recommendation accuracy (i.e., accuracy was their  only goal), nowadays many RSs models include diversity in recommendations (which thus is a further goal of RSs). In the computer science community, the introduction of diversity in RSs is justified mainly through economic reasons: diversity increases user satisfaction and, in niche markets, profits.I contend that, first, the economic justification of diversity in RSs risks reducing it to an empirical matter of preference; second, diversity is ethically relevant as it supports two autonomy rights of the user: the right to an open present and the right to be treated as an individual. So far, diversity in RSs has been morally defended only in the case of RSs of news and scholarly content: diversity is held to have a depolarizing effect in a democratic society and the scientific community and make the users more autonomous in their news choices. I provide a justification of diversity in RSs that embraces all kinds of RSs (i.e., a holistic moral defense) and is based on a normative principle founded on the agency of the user, which I call the right to be an exception to predictions. Such a right holds that the proper treatment of a RS user qua agent forbids providing them with recommendations based only on their past or similar users’ choices

Catalog (2014-2015)

A snapshot of the PCOM curriculum through the decades.https://digitalcommons.pcom.edu/catalogs/1011/thumbnail.jp

Detecting Flow Experiences in Cognitive Tasks - A Neurophysiological Approach

Das Flow-Erlebnis beschreibt einen Zustand vollständiger Aufgabenvertiefung und mühelosen Handelns, der mit Höchstleistungen, persönlichem Wachstum, sowie allgemeinem Wohlbefinden verbunden ist. Für Unternehmen stellen häufigere Flow-Erlebnisse der ArbeitnehmerInnen daher auch eine produktivitäts- und zufriedenheitsfördernde Basis dar. Vor allem da sich aktuell globale Phänomene wie die steigende Nachfrage nach Wissensarbeit und das niedrige Arbeitsengagement zuspitzen, können Unternehmen von einer Förderung von Flow profitieren. Die Unterstützung von Flow stellt allerdings aufgrund der Vielfalt von Arbeitnehmerfertigkeiten, -aufgaben, und -arbeitsplätzen eine komplexe Herausforderung dar. WissensarbeiterInnen stehen dynamischen Aufgaben gegenüber, die diverse Kompetenzen und die Kooperation mit anderen erfordern. Arbeitsplätze werden vielseitiger, indem die Grenzen zwischen ko-präsenten und virtuellen Interaktionen verschwinden. Diese Vielfalt bedeutet, dass eine solide Flow-Förderung nur durch personen-, aufgaben- und situationsunabhängige Ansätze erfolgen kann. Aus diesem Grund werden zunehmend die neurophysiologischen Grundlagen des Flow-Erlebens untersucht. Auf deren Basis könnten adaptive Neuro-Informationssysteme entwickelt werden, die mittels tragbarer Sensorik Flow kontinuierlich erkennen und fördern können. Diese Wissensbasis ist bislang jedoch nur spärlich und in stark fragmentierter Form vorhanden. Für das Individuum existieren lediglich konkurrierende Vorschläge, die noch nicht durch situations- und sensorübergreifende Studien konsolidiert wurden. Für Gruppen existiert noch fast keine Forschung zu neurophysiologischen Flow-Korrelaten, insbesondere keine im Kontext digital-mediierter Interaktionen. In dieser Dissertation werden genau diese Forschungslücken durch die situationsübergreifende Beobachtung von Flow mit tragbaren EKG und EEG Sensoren adressiert. Dabei werden zentrale Grenzen der experimentellen Flow-Forschung berücksichtigt, vor allem die Defizite etablierter Paradigmen zum kontrollierten Hervorrufen von Flow. Indem Erlebnisse in zwei kognitiven Aufgaben und mehreren Manipulationen (von Schwierigkeit, Natürlichkeit, Autonomie und sozialer Interaktion) variiert werden, wird untersucht, wie Flow intensiver hervorgerufen und wie das Erlebnis stabiler über Situationen hinweg beobachtet werden kann. Die Studienergebnisse deuten dabei insgesamt auf ein Flow-Muster von moderater physiologischer Aktivierung und mentaler Arbeitslast, von erhöhter, aufgabenorientierter Aufmerksamkeit und von affektiver Neutralität hin. Vor allem die EEG Daten zeigen ein diagnostisches Potenzial, schwächere von stärkeren Flow-Zuständen unterscheiden zu können, indem optimale und nicht-optimale Aufgabenschwierigkeiten (für Individuen und Gruppen) erkannt werden. Um das Flow-Erleben weiter zu fördern, werden geeignete Wege für zukünftige Forschung abschließend diskutiert

The Effects of Product Feature Complexity, Market Activity, and Update Scheduling on Mobile App Life Cycles

Rapid advancements in telecommunication devices and the emergence of the mobile app ecosystem have immensely impacted our lives. Innovative apps have helped improve market efficiency in agriculture, contributed to environmental sustainability through peer-to-peer sharing services, and stimulated financial inclusion in developing economies. However, mobile app developers have to deal with challenges that can hinder the app to reach its full potential. In order to achieve commercial success in the hyper-competitive business landscape where freemium business models are dominating, developers need deep understanding on how non-price operational levers such as product design, delivery, and continued service lead to user adoption. From the two essays that comprise this dissertation, the first essay aims to explain user downloads of free mobile apps during the introduction stage in the lifecycle based on app feature designs and launch timings. The second essay estimates the effect of app enhancement updates on app downloads and explores contextual factors such as update regularity, lifecycle stage, and market activity levels that may further influence the effectiveness of the enhancements. Research questions proposed in the essays are answered by statistical analysis of heteroskedasticity-based instrumental variables regression and difference-in-differences analysis on free iOS mobile game app data acquired from app market Application Programming Interface (API) that contains daily performance observations over a 3.5-year time horizon. Data extraction and sample construction relied on naive Bayes tf-idf document classification algorithms and Bass diffusion model predictions which are performed via multi-thread processing on a high-performance cluster computing (HPC) server

Efficacy of a web-based, center-based or combined physical activity intervention among older adults

peer reviewedWith more social support and environment-centered interventions being recommended in web-based interventions, this study examined the efficacy of three intervention conditions aimed at promoting physical activity (PA) in older adults. The efficacy analyses included the self-reported PA level, stage of change for PA and awareness about PA among participants. Eligible participants (N = 149; M = 65 years old, SD = 6), recruited in a unique Belgian French-speaking municipality, were randomized in four research arms for a 3-month intervention: (i) web-based; (ii) center-based; (iii) mixed (combination of web- and center-based); and (iv) control (no intervention). Web-based condition included a PA website and monthly tailored emails whereas center-based condition comprised 12 sessions (1 per week) of group exercising. With a significant increase in PA, the PA stage of change and the PA awareness at 12 months, the mixed intervention condition seemed to include the key social and motivating elements for sustainable behavior change. Center-based intervention was more likely to produce significant improvements of the PA level and the stage of change for PA change whereas web-based intervention was more likely to extend the awareness about PA

Leaving The Life: Exploring Services for Women Exiting Prostitution

Women in prostitution (WIP) are significantly more likely to experience mental health issues and trauma than the general population (Farley, 2003; Ling, Wong, Holroyd, & Gray, 2007; Rössler et al. 2010; Roxburgh, Degenhardt, & Copeland, 2008). Previous research addressing the mental health of WIP emphasizes treating trauma to help women exit, both trauma that predated entry into prostitution and trauma experienced during prostitution (Carter & Dalla, 2006; Farley, 2003). Very little research is available on services for WIP, leaving psychotherapists with limited guidance on providing effective mental health treatment. Although programs exist exclusively to assist women leaving prostitution, little is known about what services they offer or if their services are trauma-informed. Because of this dearth, this study consists of exploratory program evaluations of eight agencies that focus primary on serving WIP to understand what services are provided to this population and how services address trauma. Constructive process evaluations are guided by Program Theory (Chen, 2015) and analysis uses Constructivist Grounded Theory to begin to fill research gaps about what services are available to WIP, what services are most helpful, how trauma is addressed in services, and how services could be improved for this vulnerable population of women