• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Journal of the Korean housing association
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• v.21 no.1
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• pp.67-77
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• 2010

Citizen participation in local redevelopment has recently been regarded as essential, since progress in democracy and diversified public interests have contributed to more importance being placed on citizen participation in the implementation of public policies. While the importance of resident participation has been increasingly emphasized in principle, in reality more effort is still required in its application. We need to develop practical strategies of collecting community opinion in order to reflect it in public policy, if we are to achieve a resident and citizen-centered society. The purpose of this study is to develop an image map construction tool that can be applied to the "Maul-Mandulgi" projects as a visualized method to facilitate the exchange of opinions and work toward agreements. The tool is intended to assist public discussion by visualizing policies and plans and reducing the possibility of misunderstanding, so that residents can properly respond to the plans. Second, this study will verify the effectiveness of the tool in the application to local community workshops. The main research method is participant observation method and field study. Major findings are as follows, First, every resident who had participated in previous workshops gathered together, used the tool and represented their opinions unusually more than once. Each resident tried to make sure that other participants appropriately understood his or her opinion. The workshop finished when all participants agreed and produced a consensus. The workshop took much less time, which is in stark contrast to previous workshops in which it took significantly more time to collect opinions. Second, it proved that residents in the redevelopment area can strike a broad agreement by themselves on a method and direction for residential improvement. In previous workshops, conflicts between residents developed over the choice between the two methods, of local improvement and total demolition prior to multi-housing construction. In this study, opinions of residents were not limited to the two methods by finding a winwin solution. Third, the use of the tool kit for image map became efficient for inactive residents to develop their own opinions in regard to the direction and orientations of the residential improvement process. In addition, for those who have either no or a slight understanding of the residential improvement projects, the tool can provide access to information and knowledge. This study concludes that the developed tool for imaging of the redevelopment projection like a design game, rather than using forms of text and speech, can be a useful tool in collecting opinions and forming an agreed opinion for forthcoming residential improvement plans.

• Journal of The Korean Association For Science Education
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• v.43 no.4
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• pp.369-387
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• 2023

This study aims to interpret the experience of science research in a graduate school laboratory from the perspective of Gilles Deleuze's concepts of "agencement" and "becoming". The research was conducted as an autobiographical narrative inquiry. The research text is written in a way that tells the story of my science research experience and retells it from the perspective of Gilles Deleuze. In Deleuze's view, science research is a constantly flowing agencement. The science research agencement is composed of a mechanical agencement of various experimental tools-machines and researcher-machines as well as a collective agencement of speech acts such as biological knowledge, experiment protocols, and laboratory rules. Furthermore, science research agencement is fluid as events occur all over the agencement. Data, as a change occurring in the material dimension, is an event and sign that raises problems. It has the agency to influence agencement through an intersubjective relationship with researchers, and the meaning of data is generated in this process. The change of agencement compelled me to perform science practice. I have performed repeated science practice, meaning that my body has constantly been connected to other machines. As a result of this connection, my body has been affected, and the capacity of my body that constitutes the agencement has been augmented. In addition, I was able to be deterritorialized from the existing science research agencement and reterritorialized in a new science research agencement with data. This process of differentiation allowed me to becoming-scientist. In sum, this study provides implications for science practice-oriented education by exploring the process of becoming-scientist based on my science research experience.

• Journal of the HCI Society of Korea
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• v.7 no.2
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• pp.35-42
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• 2012

The purpose of this study was to evaluate the usability of the tablet PC-based Korean high-tech AAC(Augmentative Alternative Communication System) software. In order to develop an AAC software which is appropriate to Korean cultural/linguistic contexts and communication needs of the users, we examined the necessity and ease of use for the communication functions that are required in native Korean communication, such as polite expressions, tense expressions, negative expressions, subject-verb auto-matching, and automatic sentence generation functions, using a scenario-based user testing. We also investigated the users' needs, preferences, and satisfaction for the tablet PC-based Korean high tech AAC using a semi-structured and open questionnaires. The participants of this study were 9 special education teachers, 6 speech therapists, and 6 parents whose children had communication disabilities. The results of the usability testing of the tablet PC-based Korean high-tech AAC software presented positive responses in general, by indicating overall scores of above 4 out of 5 except in tense and negative expressions. The necessity and ease of use in the tense and negative expressions were evaluated relatively low, and it might be related to the inconsistent interface with the polite expressions. In terms of the user interface(UI), there were users' needs for clear visual feedback in the symbol selection and display, consistent interface for all functions, more natural subject-verb auto-matching, and spacing in the text within symbols. The results of the usability testing and users' feedback might serve as a guideline to compensate and improve the function and UI of the existing AAC software.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.72-79
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• 2019

This study tries to study the poetic beauty of the space deconstructed by the medium appearing in Moon Sam-seok's children's poetry to help with simultaneous education and guiding methodology. The research method is based on the assumption that semiotics spatial image is read. In other words, we intend to derive the poetic beauty of the space in which the great pole space built by is deconstructed by the intervention of by the medium term . Among Moon Sam-seok's series of works, the research text is "The Wind and the Fire," "The Wind and the Empty Bottle," "The Wind and Salt," "The Wind and the Rock." According to the study, the wind deconstructed a space that was differentiated by the presence or absence of matter into a "coexistence space." These poetic spaces symbolize poetic beauty as ideal places of life that coexist in a distinction but not discrimination. Second, the wind has eliminated the gap between alienation, suffering and solitude. In other words, the wind deconstructed poetic space produced poetic beauty with the 'space of communication' based on homogeneity of the nature of existence. In conclusion, Moon's poetic speech can be seen that he intended to express the discreteness of the poetic space as 'communication' and 'common life' by deconstructing it with deviation and convergence by introducing a medium.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.17-24
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• 2022

The article proves that the main goal of informatization of higher education institutions in the EU countries is to improve the quality of education of future specialists by introducing digital educational resources into the education process. The main tasks of informatization of education are defined. Digital educational resources are interpreted as a set of data in digital form that is applicable for use in the learning process; it is an information source containing graphic, text, digital, speech, music, video, photo and other information aimed at implementing the goals and objectives of modern education; educational resources on the Internet, electronic textbooks, educational programs, electronic libraries, etc. The creation of digital educational resources is defined as one of the main directions of informatization of all forms and levels of Education. Types of digital educational resources by educational functions are considered. The factors that determine the effectiveness of using digital educational resources in the educational process are identified. The use of digital educational resources in the training of future specialists in the EU countries is considered in detail. European countries note that digital educational resources in professional use allow you to implement a fundamentally new approach to teaching and education, which is based on broad communication, free exchange of opinions, ideas, information of participants in a joint project, on a completely natural desire to learn new things, expand their horizons; is based on real research methods (scientific or creative laboratories), allowing you to learn the laws of nature, the basics of techniques, technology, social phenomena in their dynamics, in the process of solving vital problems, features of various types of creativity in the process of joint activities of a group of participants; promotes the acquisition by teachers of various related skills that can be very useful in their professional activities, including the skills of using computer equipment and various digital technologies.

• Korean Journal of Cognitive Science
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• v.22 no.1
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• pp.57-78
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• 2011

Paraphrasing is the act of writing a text using other words without altering the meaning. Paraphrases can be used in many fields of natural language processing. In particular, paraphrases can be incorporated in machine translation in order to improve the coverage and the quality of translation. Recently, the approaches on paraphrase extraction utilize bilingual parallel corpora, which consist of aligned sentence pairs. In these approaches, paraphrases are identified, from the word alignment result, by pivot phrases which are the phrases in one language to which two or more phrases are connected in the other language. However, the word alignment is itself a very difficult task, so there can be many alignment errors. Moreover, the alignment errors can lead to the problem of selecting incorrect pivot phrases. In this study, we propose a method in paraphrase extraction that discriminates good pivot phrases from bad pivot phrases. Each pivot phrase is weighted according to its reliability, which is scored by considering the lexical and part-of-speech information. The experimental result shows that the proposed method achieves higher precision and recall of the paraphrase extraction than the baseline. Also, we show that the extracted paraphrases can increase the coverage of the Korean-English machine translation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.1-9
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• 2024

This paper analyzes the trends in generative AI technology based on patent application documents. To achieve this, we selected 5,433 generative AI-related patents filed in South Korea, the United States, and Europe from 2003 to 2023, and analyzed the data by country, technology category, year, and applicant, presenting it visually to find insights and understand the flow of technology. The analysis shows that patents in the image category account for 36.9%, the largest share, with a continuous increase in filings, while filings in the text/document and music/speech categories have either decreased or remained stable since 2019. Although the company with the highest number of filings is a South Korean company, four out of the top five filers are U.S. companies, and all companies have filed the majority of their patents in the U.S., indicating that generative AI is growing and competing centered around the U.S. market. The findings of this paper are expected to be useful for future research and development in generative AI, as well as for formulating strategies for acquiring intellectual property.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.