1,720,982 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Graph Information Processing for Artificial Intelligence
Get PDFIn the last decade, techniques for artificial intelligence (AI) has advanced tremendously, which lead to solutions to many problems that have long-troubled us. Such examples include image/video recognition, speech recognition, and 3D scenario recognition. As the tool become more and more powerful, we started to explore data types that have never been handled in an AI fashion. Graph is undoubtedly the first one that comes to mind. Many important real-life data is or can be represented as graphs or networks: social networks, communication networks, protein-protein interaction networks, molecular structures, etc. Yet very little attention has been devoted to the study of the graph information processing in terms of AI systems until the very recent few years. For centuries people have used mathematics to solve graph problems and it worked really well until recent decades. With the rapid development of Internet, the information/data available to us has grown exponentially. It makes it very difficult for conventional mathematic tools to solve new graph problem since it will just take too much time to calculate. Thus, people turned their attention to the newborn techniques (convolutional neural network (CNN), recurrent neural network (RNN), reinforcement learning (RL), etc.) of AI. And once again, AI has shown its power to us. In this work, I will present some techniques of graph information processing for AI. The work will concentrate on two different aspect of graph information processing: information processing of non-graph data and graph data. In the first part, we started with non-graph data, signals in our case. Then a conversion is employed to convert the data into graph based on the objective and nature of the data. In the second part, methods to aggregate information in graph will be illustrated. The whole report contains three researches: tag recognition of radio frequency identification (RFID) in Internet of Things (IoT), photoplethysmogram (PPG) signal based authentication system, and cancer target prediction
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Stochastic Modeling of Semantic Structures of Online Movie Reviews
Get PDFFacing the enormous volumes of data available nowadays, we try to extract useful information from the data by properly modeling and characterizing the data. In this thesis, we focus on one particular type of semantic data --- online movie reviews, which can be found on all major movie websites. Our objective is mining movie review data to seek quantifiable patterns between reviews on the same movie, or reviews from the same reviewer. A novel approach is presented in this thesis to achieve this goal. The key idea is converting a movie review text into a list of tuples, where each tuple contains four elements: feature word, category of feature word, opinion word and polarity of opinion word. Then we further convert each tuple into an 18-dimension vector. Given a multinomial distribution representing a movie review, we can systematically and consistently quantify the similarity and dependence between reviews made by the same or different reviewers using metrics including KL distance and distance correlation, respectively. Such comparisons allow us to find reviewers sharing similarity in generated multinomial distributions, or demonstrating correlation patterns to certain extent. Among the identified pairs of frequent reviewers, we further investigate the category-wise dependency relationships between two reviewers, which are further captured by our proposed ordinary least square estimation models. The proposed data processing approaches, as well as the corresponding modeling framework, could be further leveraged to develop classification, prediction, and common randomness extraction algorithms for semantic movie review data
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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