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The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. 相似文献
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In recent years, the task of translating from one language to another has attracted wide attention from researchers due to numerous practical uses, ranging from the translation of various texts and speeches, including the so-called “machine” translation, to the dubbing of films and numerous other video materials. To study this problem, we propose to use the information-theoretic method for assessing the quality of translations. We based our approach on the classification of sources of text variability proposed by A.N. Kolmogorov: information content, form, and unconscious author’s style. It is clear that the unconscious “author’s” style is influenced by the translator. So researchers need special methods to determine how accurately the author’s style is conveyed, because it, in a sense, determines the quality of the translation. In this paper, we propose a method that allows us to estimate the quality of translation from different translators. The method is used to study translations of classical English-language works into Russian and, conversely, Russian classics into English. We successfully used this method to determine the attribution of literary texts. 相似文献
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本文比较20世纪20年代后期到50年代初出版的早期汉语教材、50年代翻译的俄语教材和60年代自编教材的内容,从而分析俄语翻译教材对汉语理论力学教材的影响。研究表明,翻译教材对数学物理专业用理论力学教材影响有限,而对工程专业理论力学教材有显著影响。这些影响包括形成了静力学、运动学和动力学的教学体系,固化了运动学的处理方式,扩展了动力学的教学内容。此外还分析了21世纪翻译出版的俄语教材及其影响。
相似文献527.
推广了量子力学中关于对称性的分析,与对称性相关的守恒量相应地推广为含时守恒量;证明了单粒子(包括相对论情况)在静态均匀磁场和含时线性势中运动具有空间平移不变性;求出了波函数的变换关系和相应的含时守恒量. 相似文献
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Agnieszka Dabrowska Aleksandra Milewska Joanna Ner-Kluza Piotr Suder Krzysztof Pyrc 《Molecules (Basel, Switzerland)》2021,26(12)
Mass spectrometry (MS) used in proteomic approaches is able to detect hundreds of proteins in a single assay. Although undeniable high analytical power of MS, data acquired sometimes lead to confusing results, especially during a search of very selective, unique interactions in complex biological matrices. Here, we would like to show an example of such confusing data, providing an extensive discussion on the observed phenomenon. Our investigations focus on the interaction between the Zika virus NS3 protease, which is essential for virus replication. This enzyme is known for helping to remodel the microenvironment of the infected cells. Several reports show that this protease can process cellular substrates and thereby modify cellular pathways that are important for the virus. Herein, we explored some of the targets of NS3, clearly shown by proteomic techniques, as processed during infection. Unfortunately, we could not confirm the biological relevance of protein targets for viral infections detected by MS. Thus, although mass spectrometry is highly sensitive and useful in many instances, also being able to show directions where cell/virus interaction occurs, we believe that deep recognition of their biological role is essential to receive complete insight into the investigated process. 相似文献
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Given a two-generated group of prime-power order, we investigate the singularities of origamis whose deck group acts transitively and is isomorphic to the given group. Geometric and group-theoretic ideas are used to classify the possible strata, depending on the prime-power order. We then show that for many interesting known families of two-generated groups of prime-power order, including all regular, or powerful ones, or those of maximal class, each group admits only one possible stratum. However, we also construct examples of two-generated groups of prime-power order, which do not determine a unique stratum. 相似文献
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