305,154 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
HeatMapper Expansion
No full textExpansion of an existing visualization tool for genomic data.Software TechnologyElectrical Engineering, Mathematics and Computer Scienc
Predict Radiotherapy Plan Quality
No full textA person with cancer has several treatment options. One of which is radiotherapy. Radiotherapy is treatment of cancer with radiation. To minimize the damage to healthy tissue, radiation is applied from several directions into the body. When treating cancer with radiotherapy, the organs nearby the tumor are at high risk of getting damaged. In the treatment plan the dose to the organs at risk has to be balanced with the dose given to the target. These calculations are nowadays done by medical personnel. Although a lot of treatments succeed, without much damage to healthy tissue, a lot of treatments do serious damage to the organs at risk. Can treatment plans be optimized in terms of organ sparing? To reach optimization, several methods have been executed in order to create groups within a patient set. 115 patients of prostate cancer have been analyzed using Principal Component Analysis and Agglomerative Clustering. The data consist of Overlap Volume Histogram values of the bladder and rectum in a CSV file. Each CSV file contains 201 values. These CSVs are used as an input for both methods. This led to several figures as results. The principal component analysis showed that 80% of the data is covered by the first principal component and 92% by the first and second. Also, a scatterplot has been made, which shows the transformed data. This scatterplot shows no subgroups can be identified with the bladder and rectum data of the patient. The Agglomerative Clustering method results in six plots. A variation in linkages and connectivity has been used, but all six led to no clear distinction within the data. These results led to the conclusion that no subgroups are distinguishable based only on OVH data and no prediction can be made that optimizes radiotherapy plans based solely on OVH data of patients.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Mining e-mail content for author identification forensics
No full textWe describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation
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