1,720,973 research outputs found
Density based subspace clustering: a case study on perception of the required skill
Get PDFThis research aims to develop an improved model for subspace clustering based on density connection. The researches started with the problem were there are hidden data in a different space. Meanwhile the dimensionality increases, the farthest neighbour of data point expected to be almost as close as nearest neighbour for a wide range of data distributions and distance functions. In this case avoid the curse of dimensionality in multidimensional data and identify cluster in different subspace in multidimensional data are identified problem. However develop an improved model for subspace clustering based on density connection is important, also how to elaborate and testing subspace clustering based on density connection in educational data, especially how to ensure subspace clustering based on density connection can be used to justify higher learning institution required skill. Subspace clustering is projected as a search technique for grouping data or attributes in different clusters. Grouping done to identify the level of data density and to identify outliers or irrelevant data that will create each to cluster exist in a separate subset. This thesis proposed subspace clustering based on density connection, named DAta MIning subspace clusteRing Approach (DAMIRA), an improve of subspace clustering algorithm based on density connection. The main idea based on the density in each cluster is that any data has the minimum number of neighbouring data, where data density must be more than a certain threshold. In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. If the data have a relationship, it will be classified as a subspace. Any data on the subspace clusters will then be tested again with DBSCAN algorithms, to look back on its density until a pure subspace cluster is finally found. The study used multidimensional data, such as benchmark datasets and real datasets. Real datasets are from education, particularly regarding the perception of students’ industrial training and from industries due to required skill. To verify the quality of the clustering obtained through proposed technique, we do DBSCAN, FIRES, INSCY, and SUBCLU. DAMIRA has successfully established very large number of clusters for each dataset while FIRES and INSCY have a high failure tendency to produce clusters in each subspace. SUBCLU and DAMIRA have no un-clustered real datasets; thus the perception of the results from the cluster will produce more accurate information. The clustering time for glass dataset and liver dataset using DAMIRA method is more than 20 times longer than the FIRES, INSCY and SUBCLU, meanwhile for job satisfaction dataset, DAMIRA has the shortest time compare to SUBCLU and INSCY methods. For larger and more complex data, the DAMIRA performance is more efficient than SUBCLU, but, still lower than the FIRES, INSCY, and DBSCAN. DAMIRA successfully clustered all of the data, while INSCY method has a lower coverage than FIRES method. For F1 Measure, SUBCLU method is better than FIRES, INSCY, and DAMIRA. This study present improved model for subspace clustering based on density connection, to cope with the challenges clustering in educational data mining, named as DAMIRA. This method can be used to justify perception of the required skill for higher learning institution
Zain “The design of pre-processing multidimensional data based on component analysis
Get PDFIncreased implementation of new databases related to multidimensional data involving techniques to support efficient query process, create opportunities for more extensive research. Pre-processing is required because of lack of data attribute values, noisy data, errors, inconsistencies or outliers and differences in coding. Several types of pre-processing based on component analysis will be carried out for cleaning, data integration and transformation, as well as to reduce the dimensions. Component analysis can be done by statistical methods, with the aim to separate the various sources of data into a statistical pattern independent. This paper aims to improve the quality of pre-processed data based on component analysis. RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. The model was tested using wisconsin breast cancer datasets, lung cancer datasets and prostate cancer datasets. The result shows that the performance of the cluster vector value is higher and the processing time is shorter
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
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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