1,720,958 research outputs found
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
Global Error Propagation in the Numerical Solution of an Ordinary Differential Equation with a Discontinuity
No full textSupport Vector Classifiers in scikit-learn: Mathematical Detail, Part IV
No full textWe present mathematical detail pertaining to the one-class support vector machine, as used in scikit-learn, which can be used to identify outliers in an unlabeled dataset. We construct the primal problem, from which we derive the dual problem. We discuss the nature of the decision surface. We include an illustrative numerical example. The paper is the fourth in a series and is intended to be educational in nature.
Tunawasilisha maelezo ya hisabati yanayohusiana na mashine ya vekta ya usaidizi ya darasa moja, kama inavyotumika katika kujifunza kwa scikit, ambayo inaweza kutumika kutambua bidhaa za nje katika mkusanyiko wa data usio na lebo. Tunaunda shida ya msingi, ambayo tunapata shida mbili. Tunajadili asili ya uso wa uamuzi. Tunajumuisha mfano wa nambari wa kielelezo. Karatasi ni ya nne katika mfululizo na inakusudiwa kuwa ya elimu kwa asili.
(Translation into Swahili provided by Google Translate)
Support Vector Classifiers in scikit-learn: Mathematical Detail, Part III
No full textWe present mathematical detail pertaining to the theory of the soft-margin support vector classifier ν-SVC, as used in scikit-learn. We construct the primal problem, from which we derive the dual problem. We also show how the primal problem can be derived from the dual problem. We analyze the effect of the parameter ν, and we discuss the relationship between ν-SVC and C-SVC. We include an interesting numerical example. The paper is the third in a series and is intended to be educational in nature.
Tunawasilisha maelezo ya hisabati yanayohusiana na nadharia ya kiainishi cha vekta ya usaidizi wa ukingo laini ν-SVC, kama inavyotumika katika kujifunza-scikit. Tunaunda shida ya msingi, ambayo tunapata shida mbili. Pia tunaonyesha jinsi shida ya msingi inaweza kutolewa kutoka kwa shida mbili. Tunachambua athari za parameta ν, na tunajadili uhusiano kati ya ν-SVC na C-SVC. Tunajumuisha mfano wa nambari unaovutia. Karatasi ni ya tatu katika mfululizo na inakusudiwa kuwa ya elimu kwa asili.
(The translation into Swahili was provided by Google Translate)
Support Vector Classifiers in scikit-learn: Mathematical Detail, Part IV
No full textWe present mathematical detail pertaining to the one-class support vector machine, as used in scikit-learn, which can be used to identify outliers in an unlabeled dataset. We construct the primal problem, from which we derive the dual problem. We discuss the nature of the decision surface. We include an illustrative numerical example. The paper is the fourth in a series and is intended to be educational in nature.
Tunawasilisha maelezo ya hisabati yanayohusiana na mashine ya vekta ya usaidizi ya darasa moja, kama inavyotumika katika kujifunza kwa scikit, ambayo inaweza kutumika kutambua bidhaa za nje katika mkusanyiko wa data usio na lebo. Tunaunda shida ya msingi, ambayo tunapata shida mbili. Tunajadili asili ya uso wa uamuzi. Tunajumuisha mfano wa nambari wa kielelezo. Karatasi ni ya nne katika mfululizo na inakusudiwa kuwa ya elimu kwa asili.
(Translation into Swahili provided by Google Translate)
Support Vector Classifiers in scikit-learn: Mathematical Detail, Part II
No full textWe present mathematical detail pertaining to the theory of soft-margin support vector classifiers, designated C-SVC, as used in scikit-learn. We discuss the character of C-SVC, particularly with regard to the penalty term. We construct the primal problem and, thereafter, derive the dual problem. We introduce the notion of nonlinear classifiers and describe the so-called kernel trick. Additionally, we show how the primal problem can be derived from the dual problem. The paper is the second in a series and is intended to be educational in nature.
Tunawasilisha maelezo ya hisabati yanayohusiana na nadharia ya viainishaji vya vekta vya usaidizi wa ukingo laini, iliyoteuliwa C-SVC, kama inavyotumiwa katika kujifunza kwa scikit. Tunajadili tabia ya C-SVC, hasa kuhusu muda wa adhabu. Tunaunda shida ya msingi na, baada ya hapo, tunapata shida mbili. Tunatanguliza wazo la viainishaji visivyo vya mstari na kuelezea kinachojulikana kama hila ya kernel. Zaidi ya hayo, tunaonyesha jinsi shida ya msingi inaweza kupatikana kutoka kwa shida mbili. Karatasi ni ya pili katika mfululizo na inakusudiwa kuwa ya elimu kwa asili.
(The translation into Swahili was provided by Google Translate)
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