1,720,956 research outputs found
Big Data Clustering using Parallel Differential Evolution Algorithm
Get PDFClustering is the task of discovering group ofsimilar objects or items and there have been manyapplications for clustering such as imagesegmentation, document retrieval and data mining.The increasing volumes of information emerging bythe development of technology makes clustering ofvery large scale of data a challenging task.Differential evolution (DE) algorithm is aninnovative evolutionary algorithm (EA) for globaloptimization, where the mutation operator is basedon the distribution of solutions in the population.Clustering can be viewed as optimization problemwhere the task is finding the optimal cluster solution.To deal with clustering of huge amount of data sets,the use of classical DE is time-consuming that it isinfeasible. This paper proposes a parallel differentialevolution algorithm for clustering enormous databased on Spark framework. The proposed approachwill be efficient for large-scale data clustering
An Improved Differential Evolution Algorithm with Opposition-Based Learning for Clustering Problems
Get PDFDifferential Evolution (DE) is a popularefficient population-based stochastic optimizationtechnique for solving real-world optimizationproblems in various domains. In knowledge discoveryand data mining, optimization-based patternrecognition has become an important field, andoptimization approaches have been exploited toenhance the efficiency and accuracy of classification,clustering and association rule mining. Like otherpopulation-based approaches, the performance of DErelies on the positions of initial population which maylead to the situation of stagnation and prematureconvergence. This paper describes a differentialevolution algorithm for solving clustering problems,in which opposition-based learning (OBL) is utilizedto create high-quality solutions for initial population,and enhance the performance of clustering. Theexperimental test has been carried out on some UCIstandard datasets that are mostly used foroptimization-based clustering. According to theresults, the proposed algorithm is more efficient androbust than classical DE based clustering
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
Community Detection in Social Graph Using Nature-Inspired Based Artificial Bee Colony Algorithm with Crossover and Mutation
Get PDFMany types of social network are modelled asgraphs. Community detection has been an important researcharea in social graph analysis. Community detection can beviewed as an optimization problem. Nowadays, researchers usenature-inspired algorithms to solve optimization problem.Their goal is to find the optimal solution for a given problem.In this paper, nature-inspired based artificial bee colonyalgorithm with crossover and mutation is used to detectcommunity in social graphs. GraphX is built as a library onthe top of Spark by encoding graph as a collection of verticesand edges. Comparative studies describe that the proposedalgorithm and other nature-inspired algorithms can effectivelydetect the community structure on real world social graphs asother traditional community detection algorithms
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
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
- …
