1,722,275 research outputs found
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
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
Serum MUC-1 as a marker of disease status in multiple myeloma patients receiving thalidomide - Response to Mileshkin et al.
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Augmented contents as assistive technology to make more inclusive everyday objects for visually impaired people
Full text linkThis study investigates how to exploit technologies for making society more inclusive by increasing the usability of artefacts that may be not accessible to people with disabilities. Accessing everyday objects can be a challenge for blind and visually impaired people. Although digital calendars are available, a tangible paper-based calendar can be more suitable or preferred by users, in specific contexts. Such a calendar should be as inclusive as possible. This paper shares the experience of designing an inclusive paper-based calendar conceived in codesign sessions with blind and visually impaired users
How to make everyday objects more inclusive: a case study via remote participatory design
No full textInteracting with everyday objects remains a challenge for blind and visually impaired people who rely on assistive technology. This study investigates how to exploit Information and Communication Technology (ICT) to make everyday objects more accessible for people with visual disabilities, and help create a more inclusive society. A participatory design process including five blind and two visually impaired users was carried out in Italy, exploiting video conferencing tools with the aim of increasing the usability of everyday objects, based on visual interfaces, usually poorly accessible to sightless people. As a case study, a well-known traditional paper-based calendar was selected, since it is a very popular object used at home, at work and in social life. Although digital calendars are very popular nowadays, a tangible paper-based calendar may be more suitable or preferred by users, in specific contexts. Due to people's various needs and preferences, a set of suggestions emerged from this valuable experience in co-design sessions with technical teams and end users, which can be applied in other contexts where additional information is required
A class-specific metric learning approach for graph embedding by information granulation
No full textGraphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological and semantic information. Despite their invaluable descriptive power, their arbitrarily complex structured nature poses serious challenges when they are involved in learning systems. Typical approaches aim at building a vectorial representation of the graph in a suitable embedding space by leveraging on the selection of relevant prototypes that enable the use of common pattern recognition methods. An emerging paradigm able to synthesize prototypes in a data-driven fashion can be found in Granular Computing. Nonetheless, these methods often require a core dissimilarity measure defined directly in the graph domain that usually relies on a set of suitable parameters which are heavily problem-dependent. The automatic selection of these parameters is of utmost importance for building embedding spaces able to preserve the semantic contents between the structured and vector domains. In this paper, we propose an evolutionary-based approach for learning multiple dissimilarity measures tailored on each of the problem-related classes for the classification problem at hand. The learnt class-specific metrics contribute in synthesizing prototypes with high informative content related to each class by means of a Granular Computing approach. Such prototypes induce an embedding space where the graph classification can take place with common pattern recognition techniques for vector data. Tests conducted on publicly available datasets corroborate the effectiveness of the proposed approach both in terms of learning performances and interpretability of the model, as measured by the classification accuracy and number of meaningful prototypes considered in the synthesized model
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