scholarly journals Identifying constitutive articles of cumulative dissertation theses by bilingual text similarity. Evaluation of similarity methods on a new short text task

2021 ◽  
pp. 1-24
Author(s):  
Paul Donner

Abstract Cumulative dissertations are doctoral theses comprised of multiple published articles. For studies of publication activity and citation impact of early career researchers it is important to identify these articles and link them to their associated theses. Using a new benchmark dataset, this paper reports on experiments of measuring the bilingual textual similarity between, on the one hand, titles and keywords of doctoral theses, and, on the other hand, articles’ titles and abstracts. The tested methods are cosine similarity and L1 distance in the Vector Space Model (VSM) as baselines, the language-indifferent methods Latent Semantic Analysis (LSA) and trigram similarity, and the language-aware methods fastText and Random Indexing (RI). LSA and RI, two supervised methods, were trained on a purposively collected bilingual scientific parallel text corpus. The results show that the VSM baselines and the RI method perform best but that the VSM method is unsuitable for cross-language similarity due to its inherent monolingual bias.

2020 ◽  
Vol 2 (2) ◽  
pp. 58-70
Author(s):  
G. A. Parshutina

The article makes the case that the skills of consecutive interpretation are the key ones among professionally relevant competencies of modern specialists involved in international relations. Focusing on the specificity and complexity of the interpretation process, the author considers the issue of cross-language asymmetry.The author gives ground for making consecutive interpretation the object of analysis by emphasizing the fact that the related training modes are, on the one hand, cross-functional and multifaceted, and, on the other hand, universal. Their convenience and usefulness for both students and teachers are highlighted, since they help identify learning problems of special importance, was to fix them and elaborate new strategies for interpretation skills development.The purpose of the paper is to reveal and analyze the most typical mistakes in interpretation as well as outline methods of their prevention. The author sums up a number of theoretical sources, that serve as the main methodological basis for the analysis of the phenomena in question, and reflects on her own teaching experience at MGIMO University.The methods of analysis applied herein comprise elements of generalization and classification, contextual and semantic analysis, pragmafunctional analysis, empiric investigation through observation and experiment.The presented analysis results in the overview and the rationale of the most common translation mistakes arising in the process of students’ mastering skills of bilingual consecutive interpretation, and the set of suggested corrective exercises. The paper highlights the value of propaedeutic work and the process of building up successful learners’ activities.


2020 ◽  
Vol 39 (1) ◽  
pp. 1-39
Author(s):  
Andreas Blümel ◽  
Mingya Liu

AbstractIn the literature on relative clauses (e. g. Alexiadou et al.2000: 4), it is occasionally observed that the German complex definite determiner d-jenige (roughly ‘the one’) must share company with a restrictive relative clause, in contrast to bare determiners der/die/das (Roehrs2006: 213–215; Gunkel2006; Gunkel2007). Previous works such as Sternefeld (2008: 378–379) and Blümel (2011) treat the relative clause as a complement of D to account for its mandatory occurrence. While such syntactic analyses have intuitive appeal, they pose problems for a compositional semantic analysis.The goal of this paper is twofold. First, we report on two rating studies providing empirical evidence for the obligatoriness of relative clauses in German DPs introduced by the complex determiner d-jenige. Secondly, following Simonenko (2014, 2015), we provide an analysis of the phenomenon at the syntax-semantics interface that captures familiar (Blümel2011) as well as novel related observations. Particularly, the analysis accounts for the facts that postnominal modifiers can figure in d-jenige-DPs and that the element can have anaphoric demonstrative pronominal uses.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Camilla Gaiaschi

While witnessing a feminization of its workforce, the academic profession has experienced a process of market-based regulation that has contributed to the precarization of early career phases and introduced a managerial culture based on competition, hyper-productivity, and entrepreneurship. This paper aims to investigate the implications of these changes for female academics. A mixed model research design was used based on administrative data on the Italian academic population and qualitative interviews with life scientists within a specific academic institution. Results show that the implications of university transformations in terms of gender heterogeneity are complex. On the one hand, the increased precarization of early career stages has increased gender inequalities by reducing female access to tenured positions. On the other, the adoption of performance-based practices has mixed consequences for women, entailing both risks and opportunities, including spaces of agency which may even disrupt male-dominated hierarchies.


2019 ◽  
Vol 52 (9-10) ◽  
pp. 1289-1298 ◽  
Author(s):  
Lei Shi ◽  
Gang Cheng ◽  
Shang-ru Xie ◽  
Gang Xie

The aim of topic detection is to automatically identify the events and hot topics in social networks and continuously track known topics. Applying the traditional methods such as Latent Dirichlet Allocation and Probabilistic Latent Semantic Analysis is difficult given the high dimensionality of massive event texts and the short-text sparsity problems of social networks. The problem also exists of unclear topics caused by the sparse distribution of topics. To solve the above challenge, we propose a novel word embedding topic model by combining the topic model and the continuous bag-of-words mode (Cbow) method in word embedding method, named Cbow Topic Model (CTM), for topic detection and summary in social networks. We conduct similar word clustering of the target social network text dataset by introducing the classic Cbow word vectorization method, which can effectively learn the internal relationship between words and reduce the dimensionality of the input texts. We employ the topic model-to-model short text for effectively weakening the sparsity problem of social network texts. To detect and summarize the topic, we propose a topic detection method by leveraging similarity computing for social networks. We collected a Sina microblog dataset to conduct various experiments. The experimental results demonstrate that the CTM method is superior to the existing topic model method.


2011 ◽  
Vol 72 (3) ◽  
pp. 146-150
Author(s):  
Lynda Corby

Change is the one constant in a constantly changing world, including the world of dietetic practice. Over a 40-year career, I have witnessed and participated in many such changes. Key lessons from my early career with Manitoba Agriculture and Manitoba Health include an understanding of the power of teamwork, of the importance of communication skills, of the need for shared knowledge and expertise, and of ways to connect nutrition messages with food and eating. Later, my work as director of education in a family medicine residency program taught me the value of building a portfolio of knowledge and skills and of working with families. Similarly, my work with the Organization for Cooperation in Overseas Development led me to appreciate the need for cultural sensitivity in our work. Opportunities with Dietitians of Canada have shown me that future directions must include continued interdisciplinary development of policy and position papers. Other important challenges include determining issues relevant to various areas of dietetic practice, working to achieve Vision 2020 goals, and inspiring and nurturing new leadership among younger Dietitians of Canada members.


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