1,721,079 research outputs found
Interview with Ali Osman Taha
No full textلقاء مع وزير خارجية السودان علي عثمان محمد طه حول الإتفاق بين القوى السياسية بالسودان. أجرى هذا اللقاء إبراهيم عابدين.An interview with Sudanese Foreign Minister Ali Osman Taha about the agreement between the political forces in Sudan. Interview conducted by Ibrahim Abdeen
Interview with Ali Osman Taha
No full textمقابلة بين المراسله إيمان رافع ووزير خارجية السودان على عثمان طه، حول اتفاقيه السلام بين الحكومة السودانية وبعض الفصائل المنشقة وأهميتها لاستقرار السودان.An interview between reporter Iman Rafi and Sudanese Foreign Minister Ali Osman Taha about the peace deal reached between the Sudanese government and some dissident groups, as well as its significance for Sudan's security
An extended neuro-fuzzy approach for efficiently predicting review ratings in E-markets
No full textInternet has opened new interesting scenarios in the fields of commerce and marketing. In particular, the idea of e-commerce has enabled customers to perform their transactions in a faster and cheaper way than conventional markets, and it has allowed companies to increase their sales volume thanks to a world-wide visibility. However, one of the problems that can strongly affect the performance of any e-commerce portal is related to the quality and validity of ratings provided by customers in their past transactions. Indeed, these reviews are used to determine the extent of customers acceptance and satisfaction of a product or service and they can affect the future selling performance and market share of a company. As a consequence, an efficient analysis of customer feedback could allow e-commerce portals to improve their selling capabilities and revenue. This paper introduces an innovative computational intelligence framework for efficiently learning review ratings in e-commerce by addressing different issues involved in this significant task: the dimension and imprecision of ratings data. In particular, we integrate the techniques of Singular Value Decomposition (SVD), Fuzzy C-Means (FCM) and ANFIS and, as shown in experimental results, this synergetic approach yields better learning performance than other rating predictors based on a conventional artificial neural network and FCM algorithm. © 2014 IEEE
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
Smart information retrieval: domain knowledge centric optimization approach
Get PDFIn the age of Internet of Things (IoT), online data has witnessed significant growth in terms of volume and diversity, and research into information retrieval has become one of the important research themes in the Internet oriented data science research. In information retrieval, machine-learning techniques have been widely adopted to automate the challenging process of relation extraction from text data, which is critical to the accuracy and efficiency of information retrieval-based applications including recommender systems and sentiment analysis. In this context, this paper introduces a novel, domain knowledge centric methodology aimed at improving the accuracy of using machine-learning methods for relation classification, and then utilise Genetic Algorithms (GAs) to optimise the feature selection for the learning algorithms. The proposed methodology makes significant contribution to the processes of domain knowledge-based relation extraction including interrogating Linked Open Datasets to generate the relation classification training-data, addressing the imbalanced classification in the training datasets, determining the probability threshold of the best learning algorithm, and establishing the optimum parameters for the genetic algorithm utilised in feature selection. The experimental evaluation of the proposed methodology reveals that the adopted machine-learning algorithms exhibit higher precision and recall in relation extraction in the reduced feature space optimised by the implementation. The considered machine learning includes Support Vector Machine, Perceptron Algorithm Uneven Margin and K-Nearest Neighbours. The outcome is verified by comparing against the Random Mutation Hill-Climbing optimisation algorithm using Wilcoxon signed-rank statistical 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
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