1,721,109 research outputs found
Digital preservation and curation of self-tracking data: A position paper
Thanks to recent advances in the field of ubiquitous computing, an increasing number of users now rely on tools and apps that allow them to track specific aspects of their lives. An example are step counters and activity trackers that are promoted as unobtrusive tools to monitor our fitness levels. Interestingly, although significant research and development efforts went into improving the accuracy of these self-tracking devices, hardly any research is performed on the digital preservation of the data created. This position paper highlights challenges and opportunities arising from the digital preservation of self-tracking data
MindTheGap 2014 Beyond Single-Shot Text Queries: Bridging the Gap(s) between Research Communities
The effect of simulated contextual factors on recipe rating and nutritional intake behaviour
Despite the importance of context in Recommender Systems (RSs) more generally, and its clear applicability in the food domain, most existing research focuses on single contextual factors, and only considers simple extrinsic factors such as location and time. No RSs research has systematically explored the impact of multiple dynamic factors, or investigated the effect of emotion in determin-ing people’s eating, recipe rating and nutritional intake behaviour. To bridge these gaps, we conducted a comprehensive large-scale (n=397) crowdsourced experimental study to uncover the intri-cate relationship between various simulated contextual factors and users’ subsequent recipe rating and implied nutritional intake be-haviour. We further aimed to explore how these contextual fac-tors can be incorporated to improve recommendation performance. Four distinct types of contextual factors were investigated: seasonal, emotional, busyness and physical activity, encompassing a total of seven elements. Our findings show that people’s eating prefer-ences and the likelihood of them choosing to eat healthy recipes vary depending on the simulated context they find themselves in. Moreover, we demonstrate how these contextual features can be used to significantly improve recipe rating prediction performance. Our research has implications for the future development of food RSs, and shows that emotion-aware systems could lead to better healthy food recommendations
Implicit search trails for video recommendation
In this demo paper we demonstrate our approach and system for using implicit actions involved in video search to provide recommendations to users. The goal of this system is to improve the quality of the results that users find, and in doing so, help users to explore a large and difficult information space and help them consider search options that they may not have considered otherwise. Results of a user evaluation show that this approach achieves all of these goals
GamifIR ?14: Proceedings of the First International Workshop on Gamification for Information Retrieval
This workshop focuses on the challenges and opportunities that gamification can present for the information retrieval (IR) community. Gamification is the application of game mechanics, such as leader boards, badges or achievement points, in non-gaming environments with the aim to increase user engagement, data quality or cost effectiveness. A core aspect of gamification solutions is to infuse intrinsic motivations to participate by leveraging people's natural desires for achievement and competition. While gamification, on the one hand, is emerging as the next big thing in industry, e.g., an effective way to generate business, on the other hand, it is also becoming a major research area. However, its adoption in Information Retrieval is still in its infancy, despite the wide ranging IR tasks that may benefit from gamification techniques. These include the manual annotation of documents for IR evaluation, the participation in user studies to study interactive IR challenges, or the shift from single-user search to social search, just to mention a few
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
Appropriate Similarity Measures for Author Cocitation Analysis
We 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
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