• Journal of Korean Philosophical Society
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• v.126
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• pp.295-320
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• 2013

This thesis amis to demonstrate basically that language has the potential enough to be able to determine human's belief, attitude and behavior for Spinoza. As long as the language could be conceived with the potential to do, then it is very important in human community. And it is through dynamic and changeable, not fixed state, that meaning of this language is revealed. For Spinoza, even sign and its meaning compose one language system, but both of which are different from the other community. Because language as sign used in a specific society is articulated expression of body image, each imagination as idea is necessarily followed by its sign. This fact makes us say that language express imaginal knowledge. But language should not be considered as an means to express adequate idea of it. By the reason that order of meaning is only determined by the connection of signs, and that of meanings, each meaning of sign is not fixed. In this respect, certain meaning is changeable on account of changing new order of ideas. Through re-arranging new order of meaning, language could express more adequate and better idea than before. but what the most important fact is that it is not sufficient to express adequate idea by the means of language. Power of language determining human's belief and attitude does not depend on whether meaning of sign is true or not, but on hegemony of order of meaning. with this regard, this world could be seen as battle area of conflicting for orders of meaning. The more members accept newly created rational thought through newly arranged words, the more new views of value gain power. Solidarity of man using common language can change the world. For this purpose, first step depends on freedom of thought, freedom of deliverance of thought in which spinoza insists through A Theological - Political Treatise.

• ETRI Journal
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• v.42 no.1
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• pp.90-100
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• 2020

Named entity recognition (NER) continues to be an important task in natural language processing because it is featured as a subtask and/or subproblem in information extraction and machine translation. In Urdu language processing, it is a very difficult task. This paper proposes various deep recurrent neural network (DRNN) learning models with word embedding. Experimental results demonstrate that they improve upon current state-of-the-art NER approaches for Urdu. The DRRN models evaluated include forward and bidirectional extensions of the long short-term memory and back propagation through time approaches. The proposed models consider both language-dependent features, such as part-of-speech tags, and language-independent features, such as the "context windows" of words. The effectiveness of the DRNN models with word embedding for NER in Urdu is demonstrated using three datasets. The results reveal that the proposed approach significantly outperforms previous conditional random field and artificial neural network approaches. The best f-measure values achieved on the three benchmark datasets using the proposed deep learning approaches are 81.1%, 79.94%, and 63.21%, respectively.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.434-439
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• 2018

문체 변환 시스템을 학습하는 데 있어서 가장 큰 어려움 중 하나는 병렬 말뭉치가 부족하다는 것이다. 최근 대량의 비병렬 말뭉치만으로 문체 변환 문제를 해결하려는 많은 연구들이 발표되었지만, 아직까지도 원 문장의 정보 보존(Content preservation)과 문체 변환(Style transfer) 모두를 이루는 것이 쉽지 않은 상태이다. 특히 비교사 학습의 특성상 문체 변환과 동시에 정보를 보존하는 것이 매우 어렵다. Attention 기반의 Seq2seq 네트워크를 이용할 경우에는 과도하게 원문의 정보가 보존되어 문체 변환 능력이 떨어지기도 한다. 그리고 OOV(Out-Of-Vocabulary) 문제 또한 존재한다. 본 논문에서는 Attention 기반의 Seq2seq 네트워크를 이용하여 어절 단위의 정보 보존력을 최대한 높이면서도, 입력 문장에 효과적으로 Noise를 넣어 문체 변환 성능을 저해하는 과도한 정보 보존 현상을 막고 문체의 특성을 나타내는 어절들이 잘 변환되도록 할 뿐 아니라 OOV 문제도 줄일 수 있는 방법을 제안한다. 우리는 비교 실험을 통해 본 논문에서 제안한 방법들이 한국어 문장뿐 아니라 영어 문장에 대해서도 state-of-the-art 시스템들에 비해 향상된 성능을 보여준다는 사실을 확인하였다.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.76-82
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• 2021

An anthological analysis of known literature and historical sources is carried out in the work. It was found that the development of foreign language training of future professionals was influenced by a number of factors: socio-economic (focus on the needs of the labor market, integration into the international space, scientific and technological progress); educational (updating legal documents in the field of education, standardization of educational content, development of methods of professional development of a specialist). The historical period is analyzed and the following stages are determined: ideological (realization of ideological imperative in language and professional training of future specialists; educational-methodical (preparation according to unified curricula, reading and translation as a leading type of speech activity); integration (integration of foreign language teaching and multicultural education)), methodological (use of traditional verbal methods, standardized textbooks). Thus, the research conducted in the article indicates the periods (stages) of formation, functioning and development of foreign language education.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.55-60
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• 2022

Acceleration of the pace of life, increasing the amount of information, the emergence of "clip way of thinking" as a phenomenon has led to the problem of choosing forms of presentation of educational materials to students. One of the ways to solve this problem is to use the means of visualization of information flow, forasmuch as the thinking of modern youth is more effective in perceiving visual images than verbal means. The purpose of the research is to prove the effectiveness of the use of visualization in the process of teaching Ukrainian as a foreign language to students with clip way of thinking. The following methods have been used, namely: analysis, synthesis, comparison, systematization and generalization of scientific literature; testing and surveys; pedagogical experiment; quantitative and qualitative analysis of data, interpretation and generalization of the research results. The essence of visualization means has been revealed; the expediency of their use in the methodology of teaching foreign students the Ukrainian language has been substantiated. It has been proven that the role of Ukrainian teachers lies in taking into account all new trends in teaching, integrating computer perception of information by foreign students into teaching technology and using cognitive visualization in order to intensify the learning process.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.693-700
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• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.

• Communications of Mathematical Education
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• v.18 no.2 s.19
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• pp.9-33
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• 2004

The purpose of this paper is to contribute to the dialogue about the notion of advanced mathematical thinking by offering an alternative characterization for this idea, namely advancing mathematical activity. We use the term advancing (versus advanced) because we emphasize the progression and evolution of students' reasoning in relation to their previous activity. We also use the term activity, rather than thinking. This shift in language reflects our characterization of progression in mathematical thinking as acts of participation in a variety of different socially or culturally situated mathematical practices. We emphasize for these practices the changing nature of student' mathematical activity and frame the process of progression in terms of multiple layers of horizontal and vertical mathematizing.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.521-524
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• 1988

This paper describes BSDL(Behavioral/Structural Description Language), CDTF(Control Data Text File) and state synthesizer built for use in ICSC(InCheon Silicon Compiler). BSDL describes structral and behaviral specifications of an ASIC(Application Specific IC) for digital system design. ICSC's paser generates CDTF consists of if-then-else, arithmetic and data transfer statement according to each BSDL statement. State synthesizer generates CCG(Control Constraint Graph) in consideration of execution of statement and generates VCG (Variable Constraint Graph) in consideration use of variable generation and use of variable. Also, it involves allocating algorithm operation nodes in the data path and the control path to machine states with minimum state number and as small area as possible.

• The Journal of Bigdata
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• v.6 no.1
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• pp.63-81
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• 2021

The performance of natural language processing is rapidly improving due to the recent development and application of machine learning and deep learning technologies, and as a result, the field of application is expanding. In particular, as the demand for analysis on unstructured text data increases, interest in NLP(Natural Language Processing) is also increasing. However, due to the complexity and difficulty of the natural language preprocessing process and machine learning and deep learning theories, there are still high barriers to the use of natural language processing. In this paper, for an overall understanding of NLP, by examining the main fields of NLP that are currently being actively researched and the current state of major technologies centered on machine learning and deep learning, We want to provide a foundation to understand and utilize NLP more easily. Therefore, we investigated the change of NLP in AI(artificial intelligence) through the changes of the taxonomy of AI technology. The main areas of NLP which consists of language model, text classification, text generation, document summarization, question answering and machine translation were explained with state of the art deep learning models. In addition, major deep learning models utilized in NLP were explained, and data sets and evaluation measures for performance evaluation were summarized. We hope researchers who want to utilize NLP for various purposes in their field be able to understand the overall technical status and the main technologies of NLP through this paper.