1,721,018 research outputs found
Personalized weight loss strategies by mining activity tracker data
No full textWearable devices make self-monitoring easier by the users, who usually tend to increase physical activity and weight loss maintenance over time. But in terms of behavior adaptation to these goals, these devices do not provide specific features beyond monitoring the achievement of daily goals, such as a number of steps or miles walked and caloric outtake. The purpose of this study is twofold. By analyzing a large dataset of signals collected by these devices, we identify significant clusters of similar behavior patterns related to user physical activities. We then examine specific patterns of step count in the context of recommendation of habits that more likely give rise to weight loss effects. The evaluation of the effectiveness of these personalized recommendations, based on a comparative study, proves how a recommender system based on the reinforcement learning paradigm is able to guarantee better performance for this task by balancing the trade-off between long-term and short-term rewards
Spotting trends: The wisdom of the few
No full textSocial media sites have used recommender systems to suggest items users might like but are not already familiar with. These items are typically movies, books, pictures, or songs. Here we consider an alternative class of items - pictures posted by design-conscious individuals. We do so in the context of a mobile application in which users find "cool" items in the real world, take pictures of them, and share those pictures online. In this context, temporal dynamics matter, and users would greatly profit from ways of identifying the latest design trends. We propose a new way of recommending trending pictures to users, which unfolds in three steps. First, two types of users are identified - those who are good at uploading trends (trend makers) and those who are experienced in discovering trends (trend spotters). Second, based on what those "special few" have uploaded and rated, trends are identified early on. Third, trends are recommended using existing algorithms. Upon the complete longitudinal dataset of the mobile application, we compare our approach's performance to a traditional recommender system's. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM)
Is the sharing economy about sharing at all? A linguistic analysis of Airbnb reviews
Full text linkThe sharing economy manifesto emphasises sharing underused resources as a means to build stronger communities. This manifesto has however received strong critiques that claim these markets are all about access as opposed to sharing, and that consumers are after utilitarian, as opposed to social, value. Being able to assess whether an economy is about access or sharing has important implications for how companies operate, and compete, in this space. To help shed light onto this, we perform a linguistic analysis of the reviews that peers in a sharing economy platform leave to one another. We take Airbnb in U.S. as a use case, and identify the main themes that peers discuss in their reviews from 2012 to 2016. We find that, as one expects, utilitarian values (e.g., properties' facilities, convenience of location, business conduct) have been discussed much more frequently than social values (e.g., guest/host interactions), and, more interestingly, this gap has substantially increased over the years
Breakthroughs on Cross-Cutting Data Management, Data Analytics, and Applied Data Science
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Evaluating the efficacy of traditional fitness tracker recommendations
No full textWearable devices make self-monitoring easier by the users, who usually tend to increase physical activity and weight loss maintenance over time. But in terms of behavior adaptation to these goals, these devices do not provide specific features beyond monitoring the achievement of daily goals, such as a number of steps or miles walked, and caloric outtake. The purpose of this study is to evaluate the efficacy of the recommendations provided by traditional fitness tracker apps with respect to weight loss scenarios
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Trend makers and trend spotters in a mobile application
No full textMedia marketers and researchers have shown great interest in what becomes a trend within social media sites. Their interests have focused on analyzing the items that become trends, and done so in the context of Youtube, Twitter, and Foursquare. Here we move away from these three platforms and consider a new mobile social-networking application with which users share pictures of "cool" things they find in the real-world. Besides, we shift focus from items to people. Specifically, we focus on those who generate trends (trend makers) and those who spread them (trend spotters). We analyze the complete dataset of user interactions, and characterize trend makers (spotters) by activity, geographical, and demographic features. We find that there are key characteristics that distinguish them from typical users. Also, we provide statistical models that accurately identify who is a trend maker (spotter). These contributions not only expand current studies on trends in social media but also promise to inform the design of recommender systems, and new products. Copyright 2013 ACM
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