1,726,479 research outputs found

    Letter from William S. Cohen, U.S. Senator

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    Letter from William S. Cohen, U.S. Senator for Maine, congratulating her on her honorary doctorate in humane letters from the Rhode Island College.https://digitalcommons.usm.maine.edu/giguere-awards/1023/thumbnail.jp

    Epistemological writings: The Paul Hertz / Moritz Schlick Centenary edition of 1921. Edited by Robert S. Cohen

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    EPISTEMOLOGICAL WRITINGS: THE PAUL HERTZ / MORITZ SCHLICK CENTENARY EDITION OF 1921. EDITED BY ROBERT S. COHEN Epistemological writings: The Paul Hertz / Moritz Schlick Centenary edition of 1921. Edited by Robert S. Cohen (-

    Edwin S. Cohen

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    This is not the first time I have spoken to honor Edwin S. Cohen. I spoke at two of his retirements—at least—and in the Rotunda at both his 75th and 90th birthday celebrations. Each time, and on many other occasions over the years when I have spoken about tax law or policy in his presence, I would always steal a glance at Eddie, looking for that twinkle in his eyes, hoping to bring a smile to his face, or even an outright giggle. Today, I know I will still look, as I will for years to come, though I realize that I can no longer find his eyes, except in my own mind's eye. Eddie's absence is palpable; my heart is heavy

    Edwin S. Cohen

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    This is not the first time I have spoken to honor Edwin S. Cohen. I spoke at two of his retirements—at least—and in the Rotunda at both his 75th and 90th birthday celebrations. Each time, and on many other occasions over the years when I have spoken about tax law or policy in his presence, I would always steal a glance at Eddie, looking for that twinkle in his eyes, hoping to bring a smile to his face, or even an outright giggle. Today, I know I will still look, as I will for years to come, though I realize that I can no longer find his eyes, except in my own mind\u27s eye. Eddie\u27s absence is palpable; my heart is heavy

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    From shallow to whole-sentence semantics: semantic parsing in English and beyond

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    Humans want to speak to computers using the same language they speak to each other, rather than the symbolic and structured language machines are designed to process. Indeed, enabling a machine to process and interpret text automatically and then communicate verbally is one of the critical goals of the Natural Language Processing (NLP) and broader, the Artificial Intelligence (AI) fields. Moreover, computers are desired not to only process some written text, but also to understand it at the semantic and pragmatic level, which is further defined within the Natural Language Understanding (NLU) subfield. NLU aims at overcoming language ambiguities and complexities to enable machines to read and comprehend text. Therefore, to achieve this goal, we need computers capable of inputting text, preferably in any language, and parsing it into semantic representations which can be used as an interface between humans and computer language. To this end, a crucial issue faced by the NLP researchers is how to devise a language that is interpretable by machines and at the same time expresses the meaning of natural language, primarily known as the Semantic Parsing task. Semantic representations usually take the form of graph-like structures where words in a sentence are interconnected according to different semantic relations. Over time, this has garnered increasing attention, with researchers developing various formalisms that capture complementary aspects of meaning. Two of the most popular formalisms in NLP that capture different levels of sentence semantics are Semantic Role Labeling (SRL) — often referred to as shallow Semantic Parsing — and Abstract Meaning Representation (AMR) — a popular complete formal language for Semantic Parsing — which includes SRL, among other NLP tasks. Both SRL and AMR have been widely studied in the NLP research, counting a large number of approaches to deal with task specificities and the challenges they pose, aiming at achieving human-like performance. In particular, the majority of the SRL works rely on task-specific sequence labeling approaches. In addition, they often make use of third-party components to solve subtasks of SRL, leading to non-end-to-end approaches. We observe a similar trend in AMR related research, where aspects of meaning are treated as a different constituent in a long pipeline. These complexities, which we will elaborate on more during this thesis, may hinder the effectiveness of the models in out-of-distribution settings while also making it more challenging to integrate SRL and AMR structures in downstream tasks of NLU efficiently. Another long-standing problem in NLP is that of enabling research in languages other than English. Especially in the context of AMR , the English dependency problem is even more evident provided that it was initially designed to represent the meaning of English sentences. In this thesis we investigate the aforementioned problems in SRL, including both dependency- and span-based SRL formulations, and in AMR , including AMR parsing — the task of converting utterances into an AMR graph — and its specular counterpart AMR generation — the task of generating natural language utterances from an AMR graph. We focus on relieving the burden of complex, task-specific architectures for English SRL and AMR casting them as sequence generation problems, motivated by the overgrowing success of general-purpose sequence-to-sequence methodologies in NLP in the recent years. Furthermore, we dispose of the previously necessary third-party dependencies in AMR parsing, thus achieving a full symmetry with its dual counterpart, AMR generation. Additionally, we make use of the sequence-to-sequence paradigm and transfer learning techniques to enable cross-lingual AMR parsing — the task of learning English-centric structures to represent meaning in multiple languages

    Variations on the Author

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    “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

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    We 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
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