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Author(s):  
Svetlana V. Bylkova

Within the framework of this article, the starting point of the research is the theoretical position, according to which reports on discoveries and achievements in the field of astronomy appear as a frequency phenomenon, covered in specialized popular scientific texts. As a result, a pragmatic analysis of the source of information and ensuring access to the voices of astronomer researchers in a journalistic report is an urgent problem. The personality of the journalist acts as an intermediary between scientists and non-professional readers, whose knowledge of astronomy is limited, and the created popular science texts are a kind of communication platform for voicing the judgments that are put forward by representatives of the astronomical communities. In this regard, journalists not only supplement the reader’s knowledge in an accessible form, but also open access to the voices of representatives of the scientific and astronomical community, relying on such means as direct and indirect speech, which reveal different degrees of frequency in the first paragraph of the text and in the subsequent presentation. To systematize the actual data indicating the explicit labeling of the source of information in a popular science message, the most frequent language signals that are used by journalists in order to introduce a «foreign» voice into the text (predicates that introduce direct or indirect speech) are analyzed. As a result, models and indicators of their frequency were identified, this, in turn, provided an opportunity to trace the trends in voicing the expert astronomers’ opinions in a popular scientific text. It is established that the distribution of direct and indirect speech with explicit marking of the source of information in the first paragraph of the popular science text is not homogeneous. In this text segment, indirect speech is the most frequent, which allows the journalist to focus the reader’s attention on an unbiased vision of a scientific and astronomical event.



Author(s):  
Amit Kumar Agarwal ◽  
Akhilesh Kumar Srivastava ◽  
Shubham Singh
Keyword(s):  


2021 ◽  
Vol 20 (02) ◽  
pp. 553-596
Author(s):  
Hao Fan ◽  
Kaijun Wu ◽  
Hamid Parvin ◽  
Akram Beigi ◽  
Kim-Hung Pho

Recommender Systems ([Formula: see text]) are known in the E-Commerce ([Formula: see text]) field. They are expected to suggest the accurate goods/musics/films/items to the consumers/clients/people/users. Recent Hybrid [Formula: see text]s ([Formula: see text] have made us able to deal with the most important shortages of traditional Content-based F iltering ([Formula: see text]) and Collaborative Filtering ([Formula: see text]). Cold start, scalability and sparsity are the most important challenges to [Formula: see text] recommender systems ([Formula: see text]). [Formula: see text]s combine [Formula: see text] and [Formula: see text]. While the [Formula: see text]s that are based on memory have high accuracy, they are not scalable. Contrarily, the RSs on the basis of models have low accuracy but high scalability. Thus, aiming at dealing with cold start, scalability and sparsity challenges, [Formula: see text] is proposed to use both methods and also it has been evaluated on a real benchmark. An ontology, which is automatically created by an intelligently collected wordnet, has been employed in [Formula: see text] segment of the proposed [Formula: see text]. It has been automatically created and enhanced by an additional process. The functionality of the recommended framework has been superior to the performance of the state-of-the-art methods and the traditional [Formula: see text] and [Formula: see text] embedded in our method. Using a real dataset as a benchmark, the experimentations indicate that the proposed method not only has better performance but also has more efficacy rather than the state-of-the-art methods.



Author(s):  
Julian Höllig ◽  
Philipp Dufter ◽  
Michaela Geierhos ◽  
Wolfgang Ziegler ◽  
Hinrich Schütze


2021 ◽  
Vol 273 ◽  
pp. 11027
Author(s):  
Svetlana Bylkova ◽  
Margarita Finko ◽  
Igor Kudryashov

The journalist’s personality acts as an intermediary between scientists and non-professional readers, whose knowledge of astronomy is limited, and the created popular science texts are a kind of communicative platform for voicing judgments. In this regard, journalists not only supplement the reader’s knowledge in an accessible form, but also open access to the voices of representatives of the scientific and astronomical community, relying on such means as direct and indirect speech, which reveal different degrees of frequency in the first paragraph of the text and in the subsequent narrating. To systematize the actual data indicating the explicit labeling of the source of information in a popular science message, the most frequent language signals that are used by journalists in order to introduce a other voice into the text (predicates that introduce direct or indirect speech) were analyzed. As a result, models and indicators of their frequency were identified, which provided an opportunity to trace the trends in voicing the expert astronomers’ opinions in a popular scientific text. It is established that the distribution of direct and indirect speech with explicit marking of the source of information in the first paragraph of the popular science text is not homogeneous. In this text segment, indirect speech is the most frequent, which allows the journalist to focus the reader’s attention on an unbiased vision of a scientific event.



2020 ◽  
Vol 62 (2) ◽  
pp. 75-89
Author(s):  
Marcus Pöckelmann ◽  
Janis Dähne ◽  
Jörg Ritter ◽  
Paul Molitor

AbstractIn this paper,A shorter version of the paper appeared in German in the final report of the Digital Plato project which was funded by the Volkswagen Foundation from 2016 to 2019. [35], [28]. we present a method for paraphrase extraction in Ancient Greek that can be applied to huge text corpora in interactive humanities applications. Since lexical databases and POS tagging are either unavailable or do not achieve sufficient accuracy for ancient languages, our approach is based on pure word embeddings and the word mover’s distance (WMD) [20]. We show how to adapt the WMD approach to paraphrase searching such that the expensive WMD computation has to be computed for a small fraction of the text segments contained in the corpus, only. Formally, the time complexity will be reduced from \mathcal{O}(N\cdot {K^{3}}\cdot \log K) to \mathcal{O}(N+{K^{3}}\cdot \log K), compared to the brute-force approach which computes the WMD between each text segment of the corpus and the search query. N is the length of the corpus and K the size of its vocabulary. The method, which searches not only for paraphrases of the same length as the search query but also for paraphrases of varying lengths, was evaluated on the Thesaurus Linguae Graecae® (TLG®) [25]. The TLG consists of about 75\cdot {10^{6}} Greek words. We searched the whole TLG for paraphrases for given passages of Plato. The experimental results show that our method and the brute-force approach, with only very few exceptions, propose the same text passages in the TLG as possible paraphrases. The computation times of our method are in a range that allows its application in interactive systems and let the humanities scholars work productively and smoothly.



Author(s):  
Banerjee Partha Sarathy ◽  
Chakraborty Baisakhi ◽  
Tripathi Deepak ◽  
Gupta Hardik ◽  
Sourabh S. Kumar




2019 ◽  
Vol 5 (3) ◽  
pp. 134
Author(s):  
Ahmed Ibrahim Abed ◽  
Omar A. Shihab ◽  
Mushtaq A. Jameel

Legal language is characterized as the professional use of words. Thus, it can be said that the international law (as a result of translation and interpretation as well) has become more crucial. Therefore, legal translation has become important among the other domains of translation. This study aims at investigating the translation strategies adopted in translating the US- Iraqi security agreement from English into Arabic. So, there is a set of translation strategies that help translating the two texts properly and accurately. The translation strategies followed in translating the US- Iraqi security agreement will be investigated in the two of the two English and Arabic texts as there are many strategies in the linguistic theory of translation. Dr. As. Safi in his model covers both the local strategies which belonging to text segment and global ones that have to do with the whole text. Translation strategies are divided into general ones which deal with all types texts and specific strategies that deal with specific kinds of texts; specific ones are divided into domestication, compensation, (in kind, in place, by merging, or splitting and compensation by addition) , addition, elaboration and explication, and approximation and compromise. Thus, the text under study is a legal one and, of course, has a specific type of text; only specific strategies are applied in this study.



2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Libin Yang ◽  
Zeqing Zhang ◽  
Xiaoyan Cai ◽  
Tao Dai

With a tremendous growth in the number of scientific papers, researchers have to spend too much time and struggle to find the appropriate papers they are looking for. Local citation recommendation that provides a list of references based on a text segment could alleviate the problem. Most existing local citation recommendation approaches concentrate on how to narrow the semantic difference between the scientific papers’ and citation context’s text content, completely neglecting other information. Inspired by the successful use of the encoder-decoder framework in machine translation, we develop an attention-based encoder-decoder (AED) model for local citation recommendation. The proposed AED model integrates venue information and author information in attention mechanism and learns relations between variable-length texts of the two text objects, i.e., citation contexts and scientific papers. Specifically, we first construct an encoder to represent a citation context as a vector in a low-dimensional space; after that, we construct an attention mechanism integrating venue information and author information and use RNN to construct a decoder, then we map the decoder’s output into a softmax layer, and score the scientific papers. Finally, we select papers which have high scores and generate a recommended reference paper list. We conduct experiments on the DBLP and ACL Anthology Network (AAN) datasets, and the results illustrate that the performance of the proposed approach is better than the other three state-of-the-art approaches.



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