1,721,154 research outputs found
European Conference on Data Analysis (ECDA2015). Data Science: Foundations, Methods and Applications. 2-4 September 2015. Book of Abstracts.
Get PDFRecovery of deep-water megafaunal assemblages from hydrocarbon drilling disturbance in the Faroe-Shetland Channel
Get PDFRecovery of megabenthic assemblages from physical disturbance at the Laggan deep-water hydrocarbon drilling site in the Faroe?Shetland Channel was assessed using remotely operated vehicle quantitative video survey. Twelve undisturbed control sites and 2 well sites (A and C, disturbed 3 and 10 yr prior to this work, respectively) were analysed and compared with a previous survey immediately following disturbance at A. The megabenthic epifauna at Laggan was dominated by sponges (69.6% total fauna) represented by 20 taxa. Cnidarians (12.8%; 9 taxa) and echinoderms (7.1%; 11 taxa) were also common. Diversity was generally high and typical for the cold waters of the Faroe?Shetland Channel. Two distinct assemblages were found: one in the deeper area of the study site (also incorporating Site C), and one in the other areas (incorporating Site A). Motile faunal densities and richness were significantly elevated immediately after drilling in an area with intermediate disturbance, presumably attracted to available carcasses of organisms killed by drilling disturbance. After 3 and 10 yr, densities of motile organisms were less variable with distance, except very close to drilling where densities and richness were still reduced. Sessile faunal densities and richness increased significantly with increasing distance from drilling in all years, although both metrics were significantly higher close to drilling after 3 and 10 yr when compared to immediately after drilling. These data suggest partial megabenthic recovery between 3 and 10 yr post-disturbance. Despite this, in the area remaining completely covered by drill cuttings there were few megafauna observed even after 10 yr
Special issue on “Learning in data science: theory, methods and applications”—preface by the guest editors
Get PDFRecently, the interplay of disciplines involved in data science, most notably statistics and computer science has intensified. Impressive advances in statistical, deep, and machine learning (both supervised and unsupervised) have been achieved by developing and applying more and more complex methods for data, data stream, text, or image processing. They are now further developed and used in many fields of applications like, e.g., engineering, finance, genomics, industrial automation, industry 4.0, marketing, personalised medicine or health care, systems biology
Information and Classification : Concepts, Methods and Applications Proceedings of the 16th Annual Conference of the “Gesellschaft für Klassifikation e.V.”
No full textIn many fields of science and practice large amounts of data and informationare collected for analyzing and visualizing latent structures as orderings or classifications for example. This volume presents refereed and revised versions of 52 papers selected from the contributions of the 16th AnnualConference of the "German Classification Society". The papers are organized in three major sections on Data Analysis and Classification (1), InformationRetrieval, Knowledge Processing and Software (2), Applications and Special Topics (3). Moreover, the papers were grouped and ordered within the major sections. So, in the first section we find papers on Classification Methods, Fuzzy Classification, Multidimensional Scaling, Discriminant Analysis and Conceptual Analysis. The second section contains papers on Neural Networks and Computational Linguisticsin addition to the mentioned fields. An essential part of the third section attends to Sequence Data and Tree Reconstruction as well as Data Analysis and Informatics in Medicine. As special topics the volume presents applications in Thesauri, Archaeology, Musical Science and Psychometrics
Algorithms from and for nature and life: classification and data analysis
No full textThis volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.
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
User-Generated Content for Image Clustering and Marketing Purposes
No full textSchindler D. User-Generated Content for Image Clustering and Marketing Purposes. In: Lausen B, Van den Poel D, Ultsch A, eds. Algorithms from and for Nature and Life, Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Cham u.a.: Springer; 2013: 473-480.The analysis of images for different purposes – particularly image clustering – has been the subject of several research streams in the past. Since the 90s query by image content and, somewhat later, content-based image retrieval have been topics of growing scientific interest. A literature review shows that research on image analysis, so far, is primarily related to computer science. However, since the advent of Flickr and other media-sharing platforms there is an ever growing data base of images which reflects individual preferences regarding activities or interests. Hence, these data are promising to observe implicit preferences and complement classical efforts for several marketing purposes (see, e.g., van House 2009 or Baier and Daniel 2011). Against this background, the present paper investigates options for clustering images on the basis of personal image preferences, e.g. to use results for marketing purposes
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