1,721,639 research outputs found
An Analysis of the Relative Hardness of Reuters-21578 Subsets
No full text... benchmark for a given information retrieval (IR) task are beneficial to research on this task, since they allow different researchers to experimentally compare their own systems by comparing the results they have obtained on this benchmark. The Reuters-21578 test collection, together with its earlier variants, has been such a standard benchmark for the text categorization (TC) task throughout the last ten years. However, the benefits that this has brought about have somehow been limited by the fact that di#erent researchers have "carved" different subsets out of this collection, and tested their systems on one of these subsets only; systems that have been tested on different Reuters-21578 subsets are thus not readily comparable. In this paper we present a systematic, comparative experimental study of the three subsets of Reuters-21578 that have been most popular among TC researchers. The results we obtain allow us to determine the relative hardness of these subsets, thus establishing an indirect means for comparing TC systems that have, or will be, tested on these different subsets
Relationship between accuracy and the number of Gibbs sampling iterations on <i>Reuters-21578</i> dataset.
No full text<p>Relationship between accuracy and the number of Gibbs sampling iterations on <i>Reuters-21578</i> dataset.</p
Examining learning algorithms for text classification in digital libraries
Get PDFInformation presentation in a digital library plays important role especially in improving the usability of collections and helping users to get started with the collection. One approach is to provide an overview through large topical category hierarchies associated with the
documents of a collection. But with the growth in the amount of information, this manual classification becomes a new problem for users. The navigation through the hierarchy can
be a time-consuming and frustrating process. In this master thesis, we examine the performance of machine learning algorithms for automatic text classification. We examine three learning algorithms namely ID3, Instance Based Learning, and Naive Bayes to classify documents according to their category hierarchies. We focused on the effectiveness measurement such as recall, precision, the F1- measure, error, and the learning curve in learning a manually classified metadata collection from the Indonesian Digital Library Network (IndonesiaDLN), and we compare the results with an examination of the Reuters-21578 dataset. We summarize the algorithm that is most suitable for the digital library collection and the performance of the algorithms on these datasets
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
Syllables and Other String Kernel extensions
No full textRecently, the use of string kernels that compare documents as a string of letters has been shown to achieve good results on text classification problems. In this paper we introduce the application of the string kernel in conjunction with syllables. Using syllables shortens the representation of documents and as a result reduces computation time. Moreover syllables provide a more natural representation of text; rather than the traditional coarse representation given by the bag-of-words, or the too fine one resulting from considering individual letters only. We give some experimental results which show that syllables can be effectively used in text-categorisation problems. In this paper we also propose two extensions to the string kernel. The first introduces a new lambda-weighting scheme, where different symbols can be given differing decay weightings. This may be useful in text and other applications where the insertion of certain symbols may be known to be less significant. We also introduce the concept of 'soft matching', where symbols can match (possibly weighted by relevance) even if they are not identical. Again, this provides a method of incorporating prior knowledge where certain symbols can be regarded as a partial or exact match and contribute to the overall similarity measure for two data items
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
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