• Title/Summary/Keyword: 어휘유형

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Comparison of prosodic characteristics by question type in left- and right-hemisphere-injured stroke patients (좌반구 손상과 우반구 손상 뇌졸중 환자의 의문문 유형에 따른 운율 특성 비교)

  • Yu, Youngmi;Seong, Cheoljae
    • Phonetics and Speech Sciences
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    • v.13 no.3
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    • pp.1-13
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    • 2021
  • This study examined the characteristics of linguistic prosody in terms of cerebral lateralization in three groups of 9 healthy speakers and 14 speakers with a history of stroke (7 with left hemisphere damage (LHD), 7 with right hemisphere damage (RHD)). Specifically, prosodic characteristics related to speech rate, duration, pitch, and intensity were examined in three types of interrogative sentences (wh-questions, yes-no questions, alternative questions) with auditory perceptual evaluation. As a result, the statistically significant key variables showed flaws in production of the linguistic prosody in the speakers with LHD. The statistically significant variables were more insufficiently produced for wh-questions than for yes-no and alternative questions. This trend was particularly noticeable in variables related to pitch and speech rate. This result suggests that when Korean speakers process linguistic prosody, such as that of lexico-semantic and syntactic information in interrogative sentences, the left hemisphere seems to be superior to the right hemisphere.

Competition Relation Extraction based on Combining Machine Learning and Filtering (기계학습 및 필터링 방법을 결합한 경쟁관계 인식)

  • Lee, ChungHee;Seo, YoungHoon;Kim, HyunKi
    • Journal of KIISE
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    • v.42 no.3
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    • pp.367-378
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    • 2015
  • This study was directed at the design of a hybrid algorithm for competition relation extraction. Previous works on relation extraction have relied on various lexical and deep parsing indicators and mostly utilize only the machine learning method. We present a new algorithm integrating machine learning with various filtering methods. Some simple but useful features for competition relation extraction are also introduced, and an optimum feature set is proposed. The goal of this paper was to increase the precision of competition relation extraction by combining supervised learning with various filtering methods. Filtering methods were employed for classifying compete relation occurrence, using distance restriction for the filtering of feature pairs, and classifying whether or not the candidate entity pair is spam. For evaluation, a test set consisting of 2,565 sentences was examined. The proposed method was compared with the rule-based method and general relation extraction method. As a result, the rule-based method achieved positive precision of 0.812 and accuracy of 0.568, while the general relation extraction method achieved 0.612 and 0.563, respectively. The proposed system obtained positive precision of 0.922 and accuracy of 0.713. These results demonstrate that the developed method is effective for competition relation extraction.

Analysis on Research Trends and Proposal for Standardization of Construction & Architectural Terms in Korea (국내 건설·건축용어 연구의 동향 분석 및 표준화 제안)

  • Park, Eunha;Jeon, Jinwoo
    • The Journal of the Korea Contents Association
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    • v.15 no.5
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    • pp.620-629
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    • 2015
  • As the construction industry becomes bigger and more complicated, standardization of terms should be established between academic and industrial fields in order to accumulate and share information technology. The aim of this study is to investigate and analyze the research trends and actual usage of construction and architectural terms in Korea. For this purpose, we examined research related to construction and architectural terms by searching RISS up to August 2014. We also analyzed document types and contents of research by year. As a result, 130 research studies related to construction and architectural terms were searched. Of document types, glossary ranks the highest, followed by academic journal papers, master's theses and research reports. Research related to construction and architectural terms began in 1939, and was actively studied between the mid-1980s to the mid-1990s. Within the research, list and opinion of related construction and architectural terms are found the most frequently, followed by standardization, analysis, alteration, dictionary and wordbook, and search system of terms. Despite these efforts and research, standardization of terms has not yet been consolidated between academic and industrial fields. Therefor, we suggest six proposals in order to standardize the terms. This study is an attempt to see the trends and conditions of construction and architectural terms and to provide base-line data and an insight for future research.

Improving Recall for Context-Sensitive Spelling Correction Rules using Conditional Probability Model with Dynamic Window Sizes (동적 윈도우를 갖는 조건부확률 모델을 이용한 한국어 문맥의존 철자오류 교정 규칙의 재현율 향상)

  • Choi, Hyunsoo;Kwon, Hyukchul;Yoon, Aesun
    • Journal of KIISE
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    • v.42 no.5
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    • pp.629-636
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    • 2015
  • The types of errors corrected by a Korean spelling and grammar checker can be classified into isolated-term spelling errors and context-sensitive spelling errors (CSSE). CSSEs are difficult to detect and to correct, since they are correct words when examined alone. Thus, they can be corrected only by considering the semantic and syntactic relations to their context. CSSEs, which are frequently made even by expert wiriters, significantly affect the reliability of spelling and grammar checkers. An existing Korean spelling and grammar checker developed by P University (KSGC 4.5) adopts hand-made correction rules for correcting CSSEs. The KSGC 4.5 is designed to obtain very high precision, which results in an extremely low recall. Our overall goal of previous works was to improve the recall without considerably lowering the precision, by generalizing CSSE correction rules that mainly depend on linguistic knowledge. A variety of rule-based methods has been proposed in previous works, and the best performance showed 95.19% of average precision and 37.56% of recall. This study thus proposes a statistics based method using a conditional probability model with dynamic window sizes. in order to further improve the recall. The proposed method obtained 97.23% of average precision and 50.50% of recall.

A Contrastive Study on Korean and Chinese Passive Expression: Centered on Korean Act Subject Marks and Chinese Passive Marks (한·중 피동 표현 대조 연구 - 한국어 행위주 표지와 중국어 피동 표지 대비 중심으로 -)

  • Yu, Tong-Tong;Kim, In-Kyun
    • Cross-Cultural Studies
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    • v.47
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    • pp.217-240
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    • 2017
  • This paper is based on a comparative analysis of the Korean act subject marks '-에게(한테), -로, -에' and Chinese passive marks '被[$b{\grave{e}}i$]/?[$r{\grave{a}}ng$]/叫[$ji{\grave{a}}o$]/?[$g{\check{e}}i$]'. Each distribution's aspects and characteristics were examined and corresponding relationships were analyzed by comparison of these forms. The method of this comparative analysis focused on three aspects such as tangible characteristics of the two languages, selective restrictions on the 'act subject' or 'passive subject' in the passive expression, and constraints on the use of the act subject (passive) marks in the Korean passive expression by '받다'. In this comparative analysis Korean act subject markers '-에게(한테), -로, -에' and Chinese passive markers '被/?/叫/?' are always as an adverb in passive expression in combination with the act subject. Despite this common point, some differences were revealed relative to the use of the two languages. First, we reveal that the 'act subject' and the conjoined manner follow the passive expression according to characteristics of the two languages. In addition, the act subject marks of Korean passive expressions '에게/한테, -에/로' only serve as an investigative role. They are limited only to [${\pm}animate$] of the act subject. But Chinese passive markers '被/?/叫/?' are often restricted by [${\pm}animate$] of passive subject, existence and non-existence of act subject. In the Korean passive expression by '받다', it is used as act subject marks '에게/한테, -에/로' but the Chinese passive marks are restricted by the meaning of lexical items in a sentence.

A Study on the Considerations in Rules for Authorized Access points of Music Work (음악 저작의 전거형접근점 규칙 마련시 고려사항에 관한 연구)

  • Lee, Mihwa
    • Journal of Korean Library and Information Science Society
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    • v.49 no.4
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    • pp.147-166
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    • 2018
  • This study is to suggest the considerations in the rules for authorized access points for collocation of music work by figuring out the directions of authorized access points in FRBR, LRM, ICP 2016, RDA, and BIBFRAME, and by analyzing RDA rules for attributes and authorized access points of music works and expression and VIAF examples. First, an aggregated authorized access points were suggested as the direction of authorized access points, and original title may be selected as preferred title and the authorized access point may be based on forms in one of the languages suited to the users, if the original title is not normally suited. Second, music works's authorized access points is consisted of composer authorized access point and preferred title, and of adapter's authorized access point and preferred title in case of lacks of responsibility in composer. Also, the authorized access point of Korean traditional music work must be reviewed according to work types considering the responsibility of composer. Third, the controlled vocabularies for name of music type, medium of performance, and key could be considered for describing the attributes of work and expression. This study would be the foundation study for the authorized access point of music work, and additional research should be completed through surveying music user's need.

Variables affecting Korean word recognition: focusing on syllable shape (한글 단어 재인에 영향을 미치는 변인: 음절 형태를 중심으로)

  • Min, Suyoung;Lee, Chang H.
    • Korean Journal of Cognitive Science
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    • v.29 no.4
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    • pp.193-220
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    • 2018
  • Recent studies have demonstrated that word frequency, word length, neighborhood and word shape may have a role in visual word recognition. Shape information may affect word processing in different ways as Korean letter system works differently than that of English. The purpose of this study was to apply Gestalt's continuity principle to Korean alphabetic script(hangul), and to investigate the processing unit of hangul and to verify whether syllable shape affects word recognition in hangul. In experiment 1, three syllable words were utilized and two variables; 1) syllable types(horizontal syllable shape, e.g., "가". vertical syllable shape, e.g., "고") and 2) presenting direction (horizontal, vertical) were manipulated. Whereas "가" meets the criteria of Gestalt's continuity principle, "고" does not. Based on the result of lexical decision time, horizontal syllable shape type showed significant performance improvement, when compared to vertical syllable shape type, regardless of the presenting direction. In experiment 2, syllable types(horizontal syllable shape, vertical syllable shape) and the visual relationship between prime and target(identical, similar, different) were manipulated by using masked priming. There was a significant performance difference between the visual relationship of prime and target, and thus the effect of syllable shape was verified.

A Study on Considerations in the Authority Control to Accommodate LRM Nomen (LRM 노멘을 수용하기 위한 전거제어시 고려사항에 관한 연구)

  • Lee, Mihwa
    • Journal of Korean Library and Information Science Society
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    • v.52 no.1
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    • pp.109-128
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    • 2021
  • This paper is to explore considerations in authority control to accommodate LRM nomen entities through the literature reviews, the analysis of RDA rules, and the opinion survey of domestic catalog experts. As a result, for authority control, considerations were proposed in the aspect of nomen's attribute elements, catalog description, and MARC authority format. First, it is necessary to describe in as much detail as possible the category, the scheme, intended audience, the context of use, the reference source, the language, the script, the script conversion as the attributes of the nomen with the status of identification, note, and indifferentiated name indicators added in RDA. Second, the description method of attribute elements and relational elements of nomen can be unstructured, structured, identifier, and IRI as suggested in RDA, and vocabulary encoding scheme (VES) and string encoding scheme (SES) should be written for structured description, Also, cataloging rules for structuring authorized access points and preferred names/title should be established. Third, an additional expansion plan based on Maxwell's expansion (draft) was proposed in order to prepare the MARC 21 authority format to reflect the LRM nomen. (1) The attribute must be described in 4XX and 5XX so that the attribute can be entered for each nomen, and the attributes of the nomen to be described in 1XX, 5XX and 4XX are presented separately. (2) In order to describe the nomen category, language, script, script conversion, context of use, and date of usage as a nomen attribute, field and subfield in MARC 21 must be added. Accordingly, it was proposed to expand the subfield of 368, 381, and 377, and to add fields to describe the context of use and date of usage. The considerations in authority control for the LRM nomen proposed in this paper will be the basis for establishing an authority control plan that reflects LRM in Korea.

Korean Part-Of-Speech Tagging by using Head-Tail Tokenization (Head-Tail 토큰화 기법을 이용한 한국어 품사 태깅)

  • Suh, Hyun-Jae;Kim, Jung-Min;Kang, Seung-Shik
    • Smart Media Journal
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    • v.11 no.5
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    • pp.17-25
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    • 2022
  • Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

Intelligent VOC Analyzing System Using Opinion Mining (오피니언 마이닝을 이용한 지능형 VOC 분석시스템)

  • Kim, Yoosin;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.113-125
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    • 2013
  • Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.