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Unsupervised Korean Word Sense Disambiguation using CoreNet (코어넷을 활용한 비지도 한국어 어의 중의성 해소)

  • Han, Kijong;Nam, Sangha;Kim, Jiseong;Hahm, YoungGyun;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 2017.10a
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    • pp.153-158
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    • 2017
  • 본 논문은 한국어 어휘 의미망인 코어넷(CoreNet)을 활용한 비지도학습 방식의 한국어 어의 중의성 해소(Word Sense Dsiambiguation)에 대한 연구이다. 어의 중의성 해소의 실질적인 응용을 위해서는 합리적인 수준으로 의미 후보를 나눌 필요성이 있다. 이를 위해 동형이의어와 코어넷의 개념체계를 활용하여 의미 후보를 나누어서 진행하였으며 이렇게 나눈 것이 실제 활용에서 의미가 있음을 실험을 통해 보였다. 접근 방식으로는 문맥 속에서 서로 영향을 미치는 어휘의 의미들을 동시에 고려하여 중의성 해소를 할 수 있도록 마코프랜덤필드와 의존구조 분석을 바탕으로 한 지식 기반 모델을 사용하였다. 이 과정에서도 코어넷의 개념체계를 활용하였다. 이 방식을 통해 임의의 모든 어휘에 대해 중의성 해소를 하도록 직접 구축한 데이터 셋에 대하여 80.9%의 정확도를 보였다.

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Korean BaseNP Chunking Using Head-word of Word Phrase (어절의 중심어 정보를 이용한 한국어 기반 명사구 인식)

  • Seo, Chung-Won;Oh, Jong-Hoon;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 2003.10d
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    • pp.145-151
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    • 2003
  • 기반 명사구는 명사구 내부에 다른 명사구를 포함하지 않는 명사구로 정의된다. 이러한 기반명사구인식은 구문해석의 성능을 향상시키기 위한 방법으로 많이 사용되어 왔다. 효과적인 기반 명사구인식을 위해서는 올바른 학습자질의 선택과 적절한 문맥의 범위의 설정이 중요하다. 이러한 관점에서 기존의 연구에서는 여러 가지 학습자질과 문맥의 범위로 기반명사구를 인식하였다. 하지만 기존의 연구들에서는 학습자질로 단순한 어휘, 품사, 띄어쓰기 정보만을 사용하여 좁은 범위의 문맥정보만을 사용하였다. 본 논문에서는 한국어의 기반 명사구 인식을 위해 학습의 자질로 어절의 중심어를 사용하는 HMM모델을 제안한다. 본 논문의 방법을 통해 정확률 94.3%, 재현률 93.2%의 성능을 얻었다.

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Effects of Recommendation Selling in Family Restaurants on Customer Attitudes, Customer Satisfaction, Customer Purchase Decision Making (패밀리 레스토랑의 메뉴 권유 판매가 고객 태도, 만족, 구매 의사 결정에 미치는 영향)

  • Lee, Yeon-Jung;Ju, Hyun-Sik
    • Culinary science and hospitality research
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    • v.12 no.2 s.29
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    • pp.73-87
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    • 2006
  • The purpose of this study is to investigate if recommendation selling (methods of recommendation selling, a key word used for recommendation, and employee attitude) influences the customers' menu decision. The results of the study are as follows: 'Menu picture' and 'explanation by word' among the tools used by employees for recommendation were found to influence customers' menu decision. The words such as 'new menu' and 'special only today' used by employees for recommendation were found to influence customers' menu decision. Employees' attitude elements such as 'interesting explanation', 'dressed up tidy', 'strong intention', and 'patience' were found to influence customer's menu decision. 'Recommendation selling' in the food and beverage industry means 'employees help customers make a good decision on food and beverage service'. This study makes an important contribution to the food industry in terms of providing substantial marketing strategies.

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Unsupervised Korean Word Sense Disambiguation using CoreNet (코어넷을 활용한 비지도 한국어 어의 중의성 해소)

  • Han, Kijong;Nam, Sangha;Kim, Jiseong;Hahm, YoungGyun;Choi, Key-Sun
    • 한국어정보학회:학술대회논문집
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    • 2017.10a
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    • pp.153-158
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    • 2017
  • 본 논문은 한국어 어휘 의미망인 코어넷(CoreNet)을 활용한 비지도학습 방식의 한국어 어의 중의성 해소(Word Sense Dsiambiguation)에 대한 연구이다. 어의 중의성 해소의 실질적인 응용을 위해서는 합리적인 수준으로 의미 후보를 나눌 필요성이 있다. 이를 위해 동형이의어와 코어넷의 개념체계를 활용하여 의미 후보를 나누어서 진행하였으며 이렇게 나눈 것이 실제 활용에서 의미가 있음을 실험을 통해 보였다. 접근 방식으로는 문맥 속에서 서로 영향을 미치는 어휘의 의미들을 동시에 고려하여 중의성 해소를 할 수 있도록 마코프랜덤필드와 의존구조 분석을 바탕으로 한 지식 기반 모델을 사용하였다. 이 과정에서도 코어넷의 개념체계를 활용하였다. 이 방식을 통해 임의의 모든 어휘에 대해 중의성 해소를 하도록 직접 구축한 데이터 셋에 대하여 80.9%의 정확도를 보였다.

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Research Trend Analysis by using Text-Mining Techniques on the Convergence Studies of AI and Healthcare Technologies (텍스트 마이닝 기법을 활용한 인공지능과 헬스케어 융·복합 분야 연구동향 분석)

  • Yoon, Jee-Eun;Suh, Chang-Jin
    • Journal of Information Technology Services
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    • v.18 no.2
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    • pp.123-141
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    • 2019
  • The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

"Homeward returning": A Plebeian Romance and Naturalization of Vagrancy in John Milton's Paradise Lost

  • Cho, Hyunyoung
    • Journal of English Language & Literature
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    • v.64 no.1
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    • pp.135-150
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    • 2018
  • Focusing on the hermeneutic instability of a key word of Paradise Lost, "wander," this study attempts to situate John Milton's early modern epic in the longue $dur{\acute{e}}e$ historical transition from seignorial to capitalist mode of production, especially the displacement and reorganization of producer population, a corollary of early phase of modernization. The historic experience of vagrancy and its normalization, and the concomitant shift of the primary human sociability from given to voluntary bonds, I suggest, shape and inform Milton's early modern rewriting of the Biblical story of the fall and his revising of the heroic epic romance into a plebeian romance of a wandering, companionate couple. While building on the critical consensus on this poem's deliberate distancing from the tradition of classical epic and chivalric romance, this essay argues that Milton re-appropriates and re-channels the aspirational aspect of chivalric wandering, or mobility, for his plebeian heroes, a companionate conjugal couple. The hermeneutic instability of the word wander, this essay suggests, captures the duality of the historic experience of vagrancy, both the tragic experience of displacement and the liberational and uplifting dimension of that experience.

A Study on the Computational Model of Word Sense Disambiguation, based on Corpora and Experiments on Native Speaker's Intuition (직관 실험 및 코퍼스를 바탕으로 한 의미 중의성 해소 계산 모형 연구)

  • Kim, Dong-Sung;Choe, Jae-Woong
    • Korean Journal of Cognitive Science
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    • v.17 no.4
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    • pp.303-321
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    • 2006
  • According to Harris'(1966) distributional hypothesis, understanding the meaning of a word is thought to be dependent on its context. Under this hypothesis about human language ability, this paper proposes a computational model for native speaker's language processing mechanism concerning word sense disambiguation, based on two sets of experiments. Among the three computational models discussed in this paper, namely, the logic model, the probabilistic model, and the probabilistic inference model, the experiment shows that the logic model is first applied fer semantic disambiguation of the key word. Nexr, if the logic model fails to apply, then the probabilistic model becomes most relevant. The three models were also compared with the test results in terms of Pearson correlation coefficient value. It turns out that the logic model best explains the human decision behaviour on the ambiguous words, and the probabilistic inference model tomes next. The experiment consists of two pans; one involves 30 sentences extracted from 1 million graphic-word corpus, and the result shows the agreement rate anong native speakers is at 98% in terms of word sense disambiguation. The other pm of the experiment, which was designed to exclude the logic model effect, is composed of 50 cleft sentences.

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Effects of the Schema-Based Instructional Program on Word Problem Representation and Solving Ability (시각적 스키마 프로그램이 문장제 표상과 문제해결력에 미치는 효과)

  • Kim, Jong-Baeg;Lee, Sung-Won
    • School Mathematics
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    • v.13 no.1
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    • pp.155-173
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    • 2011
  • Problem representation is a key aspect in solving word problems. The purpose of this study was to investigate the effects of instructional program based on visual schema representing five types of word problems(Marshall, 1995). Two second grade classes of an elementary school located in Seoul were participated in this study. In experimental class, an instructional program including schema tools were suggested and administered and the other comparison group did have regular classes using diagrams and tables. Pre and post test including 15 word problems each were utilized to test students' problem solving ability. In addition, test scores on students' language ability were used to control the effects of word comprehension level on problem solving. The result revealed that experimental group showed higher problem representation and solving scores after controling the effects of pre-test. In addition, there was significant positive correlation between the ability to apply exact problem schema and problem solving results. The correlation was .58. This study showed even in the early developmental stage young students can get benefits from having instructions of word problem schema.

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A Study of Factors Influencing on Receivers' Communication Style in Internet Shopping Mall Contents (인터넷 쇼핑몰 콘텐츠에서 정보수신자의 커뮤니케이션 스타일에 미치는 영향요인에 관한 연구)

  • Chun Myung-Hwan
    • The Journal of the Korea Contents Association
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    • v.6 no.3
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    • pp.75-84
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    • 2006
  • The internet has the capabilities of supporting and facilitating several forms of consumer interaction including one-to-one, one to many, or many-to-many interactions. Especially, previous studies revealed that the Online Word-of-Mouth communication is widely used as a source of customer's information seeking and purchase decision making. Even with this importance of the Online Word-of-Mouth communication on internet, few research has systematically addressed the issue. This study investigates the effect of interpersonal communication on consumers' information search activities and develops a model that depicts the key antecedents and mediating variables of interpersonal communication in internet shopping environment. The results are as follows: First, choice uncertainty, perceived risk, and knowledge uncertainty play an important role for perceived usefulness. Second, perceived usefulness has directly affected interactive communication of consumers' communication style. Thus, it is essential for internet companies to find ways to encourage their customers to engage in word-of-mouth communication.

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Hot Keyword Extraction of Sci-tech Periodicals Based on the Improved BERT Model

  • Liu, Bing;Lv, Zhijun;Zhu, Nan;Chang, Dongyu;Lu, Mengxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.6
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    • pp.1800-1817
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    • 2022
  • With the development of the economy and the improvement of living standards, the hot issues in the subject area have become the main research direction, and the mining of the hot issues in the subject currently has problems such as a large amount of data and a complex algorithm structure. Therefore, in response to this problem, this study proposes a method for extracting hot keywords in scientific journals based on the improved BERT model.It can also provide reference for researchers,and the research method improves the overall similarity measure of the ensemble,introducing compound keyword word density, combining word segmentation, word sense set distance, and density clustering to construct an improved BERT framework, establish a composite keyword heat analysis model based on I-BERT framework.Taking the 14420 articles published in 21 kinds of social science management periodicals collected by CNKI(China National Knowledge Infrastructure) in 2017-2019 as the experimental data, the superiority of the proposed method is verified by the data of word spacing, class spacing, extraction accuracy and recall of hot keywords. In the experimental process of this research, it can be found that the method proposed in this paper has a higher accuracy than other methods in extracting hot keywords, which can ensure the timeliness and accuracy of scientific journals in capturing hot topics in the discipline, and finally pass Use information technology to master popular key words.