Mechanisms of Precedent Statements Adaptation in Chinese Internet Communication

Поступила в редакцию 28.05.2017. Принята к печати 18.04.2018.Submitted on 28 May, 2017. Accepted on 18 April, 2018.Современные тексты насыщены прецедентными высказываниями, не исключение и интернет-пространство, в частности китайская интернет-коммуникация. Однако не все пользователи сети могут обнаружить в тексте прецедентное высказывание, оценить особенности его использования и распознать источник прецедентности. В данной статье предпринята попытка рассмотреть прецедентные высказывания как источник пополнения интернет-фразеологии современного китайского языка, проанализировать формальные и смысловые способы их адаптации, а также изучить фразеосинтаксические схемы, построенные на основе прецедентных высказываний. В качестве прецедентных высказываний в китайской интернет-коммуникации выступают высказывания известных деятелей, ведущих, политиков, записи или комментарии интернет-пользователей и т. д. Те высказывания, которые без изменения формы при вторичном употреблении в интернете прибрели новое значение и стали функционировать в качестве прецедентных высказываний, можно отнести к синтаксическим фразеологизмам. Те же, в которых происходит замена лексических компонентов, могут быть отнесены к фразеосинтаксическим схемам (фразеосхемам), на основе которых выстраиваются предложения. Нередко использование синтаксических фразеологизмов и фразеосинтаксических схем, основанных на прецедентных высказываниях, продиктовано стремлением придать высказыванию юмористический оттенок, однако если высказывание затрагивает, например, политический аспект, их использование является также способом обхода достаточно жесткой в Китае интернет-цензуры. В статье также рассматриваются механизмы адаптации прецедентных высказываний к их вторичному употреблению. К таким механизмам автор относит структурные преобразования исходного высказывания, обеспечивающие, среди прочего, его смысловую и синтаксическую вариативность, а также механизмы вторичной семантизации высказывания. Проведенный анализ позволяет продемонстрировать разнообразие видов прецедентных высказываний, используемых в современной китаеязычной интернет-коммуникации, а также сформулировать вопросы, требующие дальнейшего изучения.Modern texts contain many precedent statements, and Internet space is not an exception, Chinese Internet communication in particular. However, not all Internet users can detect precedent statements in texts, measure their features, and determine the sources of precedent statements. This article is an attempt to study precedent statements as sources of modern Chinese Internet phraseology, and also analyse their formal and semantic ways of adaptation, and examine phraseosyntactic schemes (phraseoschemes) based on precedent statements. Utterances of well-known figures, famous TV hosts, politicians, as well as posts or comments of Internet users may become precedent statements in Chinese Internet communication. Statements that acquire new meanings without changing their form and begin to function as precedent statements can be considered syntactic phraseological units, while statements with replaced lexical components can be considered phraseoschemes, underlying some sentences. Quite frequently, the use of syntactic phraseological units and phraseoschemes based on precedent statements is a response to the desire to add humorous tone to an utterance, however, if it touches upon, for example, a political aspect, the use of precedent statements is also a method of bypassing quite rigid Internet censorship in China. The article examines mechanisms of precedent statements adaptation to their secondary usage. According to the author, such mechanisms include structural transformations of the original statement, which provide, among other things, its semantic and syntactic variability, and include a secondary semantisation of the statement. The analysis allows the author to demonstrate the diversity of types of precedent statements used in modern Chinese Internet communication, and formulate questions that require further study

Рекуррентные последовательности над почтикольцами

Periods and statistics of linear recurrence sequences over near-rings generated by endomorphisms of finite non-abelian extra-spexdal 2-groups are investigatexl.Исследуются периоды и статистические свойства линейных рекуррентных последовательностей над почтикольцами, порождёнными эндоморфизмами конечных неабелевых экстраспециальных 2-групп

Strict baselines for Covid-19 forecasting and ML perspective for USA and Russia

Currently, the evolution of Covid-19 allows researchers to gather the datasets accumulated over 2 years and to use them in predictive analysis. In turn, this makes it possible to assess the efficiency potential of more complex predictive models, including neural networks with different forecast horizons. In this paper, we present the results of a consistent comparative study of different types of methods for predicting the dynamics of the spread of Covid-19 based on regional data for two countries: the United States and Russia. We used well-known statistical methods (e.g., Exponential Smoothing), a "tomorrow-as-today" approach, as well as a set of classic machine learning models trained on data from individual regions. Along with them, a neural network model based on Long short-term memory (LSTM) layers was considered, the training samples of which aggregate data from all regions of two countries: the United States and Russia. Efficiency evaluation was carried out using cross-validation according to the MAPE metric. It is shown that for complicated periods characterized by a large increase in the number of confirmed daily cases, the best results are shown by the LSTM model trained on all regions of both countries, showing an average Mean Absolute Percentage Error (MAPE) of 18%, 30%, 37% for Russia and 31%, 41%, 50% for US for predictions at forecast horizons of 14, 28, and 42 days, respectively

A deep learning method based on language models for processing natural language Russian commands in human robot interaction

This paper describes the transformation process complex Russian-speaking natural language commands into a formalized graph RDF format for interaction with the robotic platfor

A scalable framework for stylometric analysis of multi-author documents

This is an accepted manuscript of a chapter published by Springer in Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science, vol 10827 on 13/05/2018, available online: https://doi.org/10.1007/978-3-319-91452-7_52 The accepted version of the publication may differ from the final published version.Stylometry is a statistical technique used to analyze the variations in the author’s writing styles and is typically applied to authorship attribution problems. In this investigation, we apply stylometry to authorship identification of multi-author documents (AIMD) task. We propose an AIMD technique called Co-Authorship Graph (CAG) which can be used to collaboratively attribute different portions of documents to different authors belonging to the same community. Based on CAG, we propose a novel AIMD solution which (i) significantly outperforms the existing state-of-the-art solution; (ii) can effectively handle a larger number of co-authors; and (iii) is capable of handling the case when some of the listed co-authors have not contributed to the document as a writer. We conducted an extensive experimental study to compare the proposed solution and the best existing AIMD method using real and synthetic datasets. We show that the proposed solution significantly outperforms existing state-of-the-art method

Recurrence sequences over near-rings

Periods and statistics of linear recurrence sequences over near-rings generated by endomorphisms of finite non-abelian extra-spexdal 2-groups are investigatexl

Mobile medical unit as a rational model of modern mobile medical formation operating in the metropolis in emergency situations

Purpose of the study. Substantiation of organizational principles of development of the health system of the population of the megalopolis in emergency situations. The article analyzes the stages of creation, testing and practical implementation of the modern organizational and staff structure of mobile medical formation and its functioning to meet the needs of the peaceful population of Moscow in Moscow pre-hospital period (2013-2017).Materials and methods. A survey of 112 respondents from 57 industry-specific metropolitan organizations and enterprises of the state healthcare system was conducted on the main indicators of the activities of institutions involved in the formation of a mobile medical unit. The result of this questionnaire was an assessment of the personnel potential of outpatient polyclinic establishments-shapers of mobile medical units, as well as the provision of full-time property and material resources of organizations and enterprises of the Moscow City Health Department involved in their formation. 24 research exercises were conducted on the formation and use of mobile medical teams to eliminate the health consequences of emergencies.Results. The article considers the issues of resource support of organizations and enterprises of the state healthcare system of Moscow. The calculation of the internal reserves of outpatient clinics of the Moscow Department of Health has been prepared, reflecting the personnel potential of the medical organizations that form the units. Research exercises have been carried out on the formation of mobile medical units, the issuance of medical equipment and sanitary equipment for them from medical warehouses, as well as the functioning of the units of mobile medical units during the mass arrival of people of various profiles.Conclusion. The study showed that the organizational foundations in the field of medical support for the population in emergencies make it possible to ensure the formation of a mobile medical unit with labor and material resources with the maximum use of internal reserves of regional health care. The proposed model of the organizational structure of a modern medical formation is an alternative to the bulky and inactive first aid unit that has existed for more than 40 years

On the applicability of STDP-based learning mechanisms to spiking neuron network models

The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition

Extraction of the relations among significant pharmacological entities in Russian-language reviews of internet users on medications

Nowadays, the analysis of digital media aimed at prediction of the society’s reaction to particular events and processes is a task of a great significance. Internet sources contain a large amount of meaningful information for a set of domains, such as marketing, author profiling, social situation analysis, healthcare, etc. In the case of healthcare, this information is useful for the pharmacovigilance purposes, including re-profiling of medications. The analysis of the mentioned sources requires the development of automatic natural language processing methods. These methods, in turn, require text datasets with complex annotation including information about named entities and relations between them. As the relevant literature analysis shows, there is a scarcity of datasets in the Russian language with annotated entity relations, and none have existed so far in the medical domain. This paper presents the first Russian-language textual corpus where entities have labels of different contexts within a single text, so that related entities share a common context. therefore this corpus is suitable for the task of belonging to the medical domain. Our second contribution is a method for the automated extraction of entity relations in Russian-language texts using the XLM-RoBERTa language model preliminarily trained on Russian drug review texts. A comparison with other machine learning methods is performed to estimate the efficiency of the proposed method. The method yields state-of-the-art accuracy of extracting the following relationship types: ADR–Drugname, Drugname–Diseasename, Drugname–SourceInfoDrug, Diseasename–Indication. As shown on the presented subcorpus from the Russian Drug Review Corpus, the method developed achieves a mean F1-score of 80.4% (estimated with cross-validation, averaged over the four relationship types). This result is 3.6% higher compared to the existing language model RuBERT, and 21.77% higher compared to basic ML classifiers