Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario

Item cold-start is a classical issue in recommender systems that affects anime and manga recommendations as well. This problem can be framed as follows: how to predict whether a user will like a manga that received few ratings from the community? Content-based techniques can alleviate this issue but require extra information, that is usually expensive to gather. In this paper, we use a deep learning technique, Illustration2Vec, to easily extract tag information from the manga and anime posters (e.g., sword, or ponytail). We propose BALSE (Blended Alternate Least Squares with Explanation), a new model for collaborative filtering, that benefits from this extra information to recommend mangas. We show, using real data from an online manga recommender system called Mangaki, that our model improves substantially the quality of recommendations, especially for less-known manga, and is able to provide an interpretation of the taste of the users.Comment: 6 pages, 3 figures, 1 table, accepted at the MANPU 2017 workshop, co-located with ICDAR 2017 in Kyoto on November 10, 201

Resolving Cold Start Problem Using User Demographics and Machine Learning Techniques for Movie Recommender Systems

There is a substantial increase in demand for recommender systems which have applications in a variety of domains. The goal of recommendations is to provide relevant choices to users. In practice, there are multiple methodologies in which recommendations take place like Collaborative Filtering (CF), Content-based filtering and Hybrid approach. For this paper, we will consider these approaches to be traditional approaches. The advantages of these approaches are in their design, functionality and efficiency. However, they do suffer from some major problems such as data sparsity, scalability and cold start to name a few. Among these problems, cold start is an intriguing area which has been plaguing recommender systems. Cold start problem occurs when the recommender system is not able to recommend new users/items since there is data sparsity. Researchers have formulated innovative techniques to alleviate cold start and the existing research conducted in this area is tremendous since the problem materializes in different use cases. Cold start is categorized into three problems. The first problem is when new users needs product recommendations from the system. The second problem is when new products listed in the system need to be recommended to existing users. The last problem is when new users and new products are present and the recommender engine needs to generate relevant recommendations. In this thesis, we concentrate on the first problem, where a user who is completely new to the system needs quality recommendations. We use a movie recommendation platform as our use case to analyze user demographics and find similarities between existing and new users to produce relevant recommendations

Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems

International audienceFactorization machines (FMs) are a powerful tool for regression and classification in the context of sparse observations, that has been successfully applied to collaborative filtering, especially when side information over users or items is available. Bayesian formulations of FMs have been proposed to provide confidence intervals over the predictions made by the model, however they usually involve Markov-chain Monte Carlo methods that require many samples to provide accurate predictions, resulting in slow training in the context of largescale data. In this paper, we propose a variational formulation of factorization machines that allows us to derive a simple objective that can be easily optimized using standard mini-batch stochastic gradient descent, making it amenable to large-scale data. Our algorithm learns an approximate posterior distribution over the user and item parameters, which leads to confidence intervals over the predictions. We show, using several datasets, that it has comparable or better performance than existing methods in terms of prediction accuracy, and provide some applications in active learning strategies, e.g., preference elicitation techniques

The Ticker, April 10, 2000

The Ticker is the student newspaper of Baruch College. It has been published continuously since 1932, when the Baruch College campus was the School of Business and Civic Administration of the City College of New York

The Art of Movies

Movie is considered to be an important art form; films entertain, educate, enlighten and inspire audiences. Film is a term that encompasses motion pictures as individual projects, as well as — in metonymy — the field in general. The origin of the name comes from the fact that photographic film (also called filmstock) has historically been the primary medium for recording and displaying motion pictures. Many other terms exist — motion pictures (or just pictures or “picture”), the silver screen, photoplays, the cinema, picture shows, flicks — and commonly movies

The Moving Page

This paper investigates transitional states of spaces between images, moving images, and the use of sketchbook/page works through a questioning and auto-ethnographic approach to research and practice. Viewing illustration as a refexive space, the investigations demonstrate exchangesbetween authorship, interaction, narrative, time, and space. Valuing the ‘in-between’ states that exist between the unfnished and fnished, the research questions notions of in-fux, moving, nebulous states. Through alternative publishing forms, the research concerns dissemination through emerging digital platforms

The Moving Page

This paper investigates transitional states of spaces between images, moving images, and the use of sketchbook/page works through a questioning and auto-ethnographic approach to research and practice. Viewing illustration as a refexive space, the investigations demonstrate exchangesbetween authorship, interaction, narrative, time, and space. Valuing the ‘in-between’ states that exist between the unfnished and fnished, the research questions notions of in-fux, moving, nebulous states. Through alternative publishing forms, the research concerns dissemination through emerging digital platforms

Neoliberalism and the cultural and political dispositions and practises of millennials in London and LA: a socio-cognitive analysis

This thesis explores the everyday experiences and aspirations of young people living in Los Angeles and London, focusing on their cultural and political dispositions, emotions, thoughts and practices, and how these converge with, and diverge from, the dominant neoliberal discourses they are surrounded by. The contemporary literature on youth and youth politics tends to view young people as active and cognizant agents in the reproduction of socio-cultural and political-economic institutions, discourses, and practices. Applying a socio-cognitive approach to the analysis of interview data, ethnographic observations, and media-cultural texts, this thesis contends that these bodies of literature neglect the unconscious dimensions of young people’s practices, and in particular, that insufficient emphasis is placed on how these contribute to the reproduction of neoliberalism. It argues that, if the literature on youth is to adequately conceptualize and represent young people and their roles in social reproduction, then research explorations must attend to these unconscious dimensions. As this thesis will demonstrate, doing so facilitates and enriches analyses of the ways in which different institutional settings influence, constrain, and enable young people, and of some of the ways that young people contest, internalize, and negotiate between the dominant societal discourses presented to them. The thesis also explores some of the lessons that a socio-cognitive approach to youth culture and politics can contribute to the work of critical educators concerned with progressive social change. It argues that critical and progressive educators must incorporate socio-cognitive insights into their practices in order to tackle the potential dispositional barriers which may hinder the realisation of the political objectives of critical and progressive pedagogy

Always at Home in the Past. Exploring Nostalgia in the Graphic Novel

My project deals with the aesthetics of nostalgia in a corpus of graphic novels. It starts by investigating the critical framework regarding nostalgia, which I analyze from a historical, psychological, philosophical and sociological perspective, giving particular attention to the implications it has for present times. It goes on to apply media-driven approaches about nostalgia to comic studies, trying to build a typology of the ways nostalgia may be seen as a two-phased, interactive articulation of comic production (of which I highlight motifs, style and structure) and reception (which I regrouped under the labels of readers, fans and collectors). Finally, I proceed to some close readings of key primary texts (graphic novels) to test my hypothesis in practice and draw my conclusions