1,720,966 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
Methods of artificial intelligence in procurement: A conceptual literature review
No full textArtificial intelligence is a key technology for procurement and its usage is still in its infancy. This work builds upon literature reviews on big data analytics in supply chain management (Min, 2010, Waller and Fawcett, 2013, Souza, 2014, Gunasekaran et al., 2017, Nguyen et al., 2017) focusing on artificial intelligence in procurement. 174 relevant publications have been identified based on a keyword search and consecutive snowball search. These are classified along the procurement process in eleven use case clusters and enriched with practical ideas. Their business value and ease of implementation are assessed through interviews to derive a research agenda
KI 2021 DC: AI Methods in Procurement
No full textArtificial intelligence is a research area that attempts to design mechanisms allowing machines to develop intelligent behavior. It is a key technology for procurement and its usage is still in its infancy. For instance, the Volkswagen "Procurement Strategy 2025" stresses the potential of artificial intelligence to optimize processes and structures-and this applies to the automotive industry and other procurement organizations worldwide. Yet, only a few have successfully integrated artificial intelligence methods into their operations and across their supply chains but is recently starting to emerge. This constitutes a research opportunity on how artificial intelligence increases its performance. The Ph.D. is set up as external doctoral research supported by Porsche and the Volkswagen AutoUni in cooperation with the University of Mannheim. The research goal is to examine and exploit ideas on how methods of artificial intelligence can be utilized in the procurement function. Procurement is often one of the last functions to be digitized. However, it must keep up in the race against the capabilities of our negotiation partners in the sales organizations of our suppliers worldwide.
The early career research consortium has provided young researchers from any subject area within AI with the opportunity to present their ideas and receive feedback at an early stage of at their scientific work. We have invited young researchers to present their research and established connections with new researchers.
The submitted abstracts and the presentations are in this upload for which permission to publish has been granted.
The Early Career Research Consortium was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2176 ’Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures’, project no. 390893796
Supplier selection with AI-based TCO models: Cost prediction case study in an automotive OEM
No full textThe goal of this research is to understand more clearly the lifecycle costs of supplier selection using methods of artificial intelligence (AI) with a total cost of ownership (TCO) model to reduce uncertainty and make better decisions. AI is a key technology for operations management and its usage is still in its infancy. Few have successfully integrated AI methods into their operations and across their supply chains but are recently starting to emerge. The research is driven by the question of how to reduce uncertainty to provide better information for selecting the right supplier. A case study is conducted at a German automotive manufacturer based on three interlinked data sets. These include: 1. Naïve algorithm models are evaluated as baselines for quality of cost prediction based on supplier selection nomination. 2. Engineering and production changes are analyzed since they often lead to price increases. 3. Cost breakdowns are considered, as they are applicable during several lifecycle phases. For the last 50 years, AACE International and the project management community have made significant contributions to increase the maturity in the practice of project management and control. This continuous commitment applies to remain resilient in the era of data science. This study suggests practical ways to break down uncertainty into a measurable quantity. References are drawn from the Total Cost Management Framework and the applicability is discussed to other settings such as construction, aerospace, defense, and public procurement where considerable related research is conducted. The work confirms previous research that in particular regression trees and Bayesian optimization can reduce the uncertainty inherent in supplier selection more than previously utilized methods
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