• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.189-197
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• 2022

Today, we are exposed to various text-based media such as newspapers, Internet articles, and SNS, and the amount of text data we encounter has increased exponentially due to the recent availability of Internet access using mobile devices such as smartphones. Collecting useful information from a lot of text information is called text analysis, and in order to extract information, it is performed using technologies such as Natural Language Processing (NLP) for processing natural language with the recent development of artificial intelligence. For this purpose, a morpheme analyzer based on everyday language has been disclosed and is being used. Pre-learning language models, which can acquire natural language knowledge through unsupervised learning based on large numbers of corpus, are a very common factor in natural language processing recently, but conventional morpheme analysts are limited in their use in specialized fields. In this paper, as a preliminary work to develop a natural language analysis language model specialized in the railway field, the procedure for construction a corpus specialized in the railway field is presented.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.92-98
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• 2024

The current software industry has an emerging issue with natural language-based requirement specifications. However, the accuracy of such requirement analysis remains a concern. It is noted that most errors still occur at the requirement specification stage. Defining and analyzing requirements based on natural language has become necessary. To address this issue, the linguistic theories of Chomsky and Fillmore are applied to the analysis of natural language-based requirements. This involves identifying the semantics of morphemes and nouns. Consequently, a mechanism was proposed for extracting object state designs and automatically generating code templates. Building on this mechanism, I suggest generating natural language-based comic images. Utilizing state diagrams, I apply changes to the states of comic characters (protagonists) and extract variations in their expressions. This introduces a novel approach to comic image generation. I anticipate highly productive comic creation by applying software processes to Cartoon ART.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.688-702
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• 1998

In this paper, we propose sign language morpheme generation rule corresponding to morpheme analysis for each part of speech. Korean natural sign language has extremely limited vocabulary, and the number of grammatical components eing currently used are limited, too. In this paper, therefore, we define natural sign language grammar corresponding to Korean language grammar in order to translate natural Korean language sentences to the corresponding sign language. Each phrase should define sign language morpheme generation grammar which is different from Korean language analysis grammar. Then, this grammar is applied to morpheme analysis/combination rule and sentence structure analysis rule. It will make us generate most natural sign language by definition of this grammar.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.5-15
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• 1997

This paper mentions a fault tree analysis using not probability but natural language and fuzzy theory, Reliability estimate of each basic event and dependence level estimate among subsystems are expressed by linguistic terms. Analysis results are also expressed by natural language. The meaning of linguistic terms is expressed by a fuzzy set. In the presented analysis approach parametrized operations of fuzzy sets are considered so that analyst's subjectivity can be introduced into the analysis. This paper gives the Chernobyl accident as an example of the fuzzy fault tree analysis using linguistic terms.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.100-106
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• 2021

Over the past few decades, natural language processing research has not made much. However, the widespread use of deep learning and neural networks attracted attention for the application of neural networks in natural language processing. Sentiment analysis is one of the challenges of natural language processing. Emotions are things that a person thinks and feels. Therefore, sentiment analysis should be able to analyze the person's attitude, opinions, and inclinations in text or actual text. In the case of emotion analysis, it is a priority to simply classify two emotions: positive and negative. In this paper we propose the deep learning based sentimental analysis system according to various optimizer that is SGD, ADAM and RMSProp. Through experimental result RMSprop optimizer shows the best performance compared to others on IMDB data set. Future work is to find more best hyper parameter for sentimental analysis system.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.537-555
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• 2021

Many researchers have carried out studies related to programming languages since the beginning of computer science. Besides programming with traditional programming languages (i.e., procedural, object-oriented, functional programming language, etc.), a new paradigm of programming is being carried out. It is programming with natural language. By programming with natural language, we expect that it will free our expressiveness in contrast to programming languages which have strong constraints in syntax. This paper surveys the approaches that generate source code automatically from a natural language description. We also categorize the approaches by their forms of input and output. Finally, we analyze the current trend of approaches and suggest the future direction of this research domain to improve automatic code generation with natural language. From the analysis, we state that researchers should work on customizing language models in the domain of source code and explore better representations of source code such as embedding techniques and pre-trained models which have been proved to work well on natural language processing tasks.

• Journal of Society of Preventive Korean Medicine
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• v.17 no.2
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• pp.179-187
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• 2013

Objectives : In many cases, patient's symptoms have been recorded on EMR in natural language instead of medical terminologies. It is possible to build a database by analyzing the symptoms of Korean Medicine(KM) that indicates patient's symptoms in natural language. Using the database, when doctors record patient's symptoms on EMR in natural language, conversely it'll be also possible to extract the symptoms of KM from those natural language. The database will enhance the value of EMR as a medical data. Methods : In this study, we aimed to make data structure of the terminologies that represent the symptoms of KM. The data structure is combinations of smallest unit in natural language. We made the database by analyzing morpheme of the natural language to express the symptoms of KM. Results & Conclusions : By classifying the natural language in 15 features, we made the structure of concept and the data available for morphological analysis.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.49-59
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• 2000

The majority of work done to date on natural language processing has focused on analysis and understanding of language, thus natural language generation had been relatively less attention than understanding, And people even tends to regard natural language generation CIS a simple reverse process of language understanding, However, need for natural language generation is growing rapidly as application systems, especially multi-language machine translation systems on the web, natural language interface systems, natural language query systems need more complex messages to generate, In this paper, we propose an algorithm to generate more flexible and natural sentence using lexical functions of Igor Mel'uk (Mel'uk ＆ Zholkovsky, 1988) and systemic grammar.

• The Journal of Information Systems
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• v.25 no.4
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• pp.121-139
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• 2016

Purpose In this study, we propose the special purposed R package named ""new_Noun()" to process nonstandard texts appeared in various social networks. As the Big data is getting interested, R - analysis tool and open source software is also getting more attention in many fields. Design/methodology/approach With more than 9,000 R packages, R provides a user-friendly functions of a variety of data mining, social network analysis and simulation functions such as statistical analysis, classification, prediction, clustering and association analysis. Especially, "KoNLP" - natural language processing package for Korean language - has reduced the time and effort of many researchers. However, as the social data increases, the informal expressions of Hangeul (Korean character) such as emoticons, informal terms and symbols make the difficulties increase in natural language processing. Findings In this study, to solve the these difficulties, special algorithms that upgrade existing open source natural language processing package have been researched. By utilizing the "KoNLP" package and analyzing the main functions in noun extracting command, we developed a new integrated noun processing package "new_Noun()" function to extract nouns which improves more than 29.1% compared with existing package.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.