• Title/Summary/Keyword: Natural language process

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Statistical Ranking Recommendation System of Hangul-to-Roman Conversion for Korean Names (한글-로마자 인명 변환의 통계적 순위 추천 시스템)

  • Lee, Jung-Hun;Kim, Minho;Kwon, Hyuk-Chul
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1269-1274
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    • 2017
  • This paper focuses on the Hangul-to-roman conversion of Korean names. The proposed method recognizes existing notation and provides results according to the frequency of use. There are two main reasons for the diversity in Hangul-to-roman name conversion. The first is the indiscreet use of varied notation made domestically and overseas. The second is the customary notation of current notation. For these reasons, it has become possible to express various Roman characters in Korean names. The system constructs and converts data from 4 million people into a statistical dictionary. In the first step, the person's name is judged through a process matching the last name. In the second step, the first name is compared and converted in the statistical dictionary. In the last step, the syllables in the name are compared and converted, and the results are ranked according to the frequency of use. This paper measured the performance compared to the existing service systems on the web. The results showed a somewhat higher performance than other systems.

A Transfer Learning Method for Solving Imbalance Data of Abusive Sentence Classification (욕설문장 분류의 불균형 데이터 해결을 위한 전이학습 방법)

  • Seo, Suin;Cho, Sung-Bae
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1275-1281
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    • 2017
  • The supervised learning approach is suitable for classification of insulting sentences, but pre-decided training sentences are necessary. Since a Character-level Convolution Neural Network is robust for each character, so is appropriate for classifying abusive sentences, however, has a drawback that demanding a lot of training sentences. In this paper, we propose transfer learning method that reusing the trained filters in the real classification process after the filters get the characteristics of offensive words by generated abusive/normal pair of sentences. We got higher performances of the classifier by decreasing the effects of data shortage and class imbalance. We executed experiments and evaluations for three datasets and got higher F1-score of character-level CNN classifier when applying transfer learning in all datasets.

On the Development of Animated Tutoring Dialogue Agent for Elementary School Science Learning (초등과학 수업을 위한 애니메이션 기반 튜터링 다이얼로그 에이전트 개발)

  • Jeong, Sang-Mok;Han, Byeong-Rae;Song, Gi-Sang
    • Journal of The Korean Association of Information Education
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    • v.9 no.4
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    • pp.673-684
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    • 2005
  • In this research, we have developed a "computer tutor" that mimics the human tutor with animated tutoring dialog agent and the agent was integrated to teaching-learning material for elementary science subject. The developed system is a natural language based teaching-learning system using one-to-one dialogue. The developed pedagogical dialogue teaching-learning system analysis student's answer then provides appropriate answer or questions after comparing the student's answer with elementary school level achievement. When the agent gives either question or answer it uses the TTS(Text-to-Speech) function. Also the agent has an animated human tutor face for providing more human like feedback. The developed dialogue interface has been applied to 64 6th grade students. The test results show that the test group's average score is higher than the control group by 10.797. This shows that unlike conventional web courseware, our approach that "ask-answer" process and the animated character, which has human tutor's emotional expression, attracts students and helps to immerse to the courseware.

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An Implementation of Mathematics Editor Using SGML Notation (SGML 표기법을 이용하는 수식 편집기의 설계 및 구현)

  • Kim, Tae-Hoon;Hyun, Deuk-Chang;Lee, Soo-Youn
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.5
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    • pp.1082-1092
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    • 1996
  • The design of distrbuted systems is difficult to achieve as the execution patterns of distrbuted systems are typically more complex than those of non- distributed systems. Thus, research toward the development of design methods for distributed systems is quitely needed. As object-oriented systems and distrbuted systems share similar properties, the combination of these two is somehow natural. In this work, a design of distributed systems is introduced. The goal of the method in this paper is to provide assistance to the process of specifying a formal object- oriented specification from graphical representation specification inputs such as data flow diagrams, state transition diagrams and Petri nets. It addresses the extraction of objects, operations and reationshipsfrom the problem domain with emphasis on the specification of the characteristics of distributed systems. This object identification method is supported by a knowledge base that provides for the automated analysis and reasoning about objects and their relationsships. The final object model is represented in a format which provides a formal mechanism for reprsenting the object information.

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Unsupervised Motion Learning for Abnormal Behavior Detection in Visual Surveillance (영상감시시스템에서 움직임의 비교사학습을 통한 비정상행동탐지)

  • Jeong, Ha-Wook;Chang, Hyung-Jin;Choi, Jin-Young
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.5
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    • pp.45-51
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    • 2011
  • In this paper, we propose an unsupervised learning method for modeling motion trajectory patterns effectively. In our approach, observations of an object on a trajectory are treated as words in a document for latent dirichlet allocation algorithm which is used for clustering words on the topic in natural language process. This allows clustering topics (e.g. go straight, turn left, turn right) effectively in complex scenes, such as crossroads. After this procedure, we learn patterns of word sequences in each cluster using Baum-Welch algorithm used to find the unknown parameters in a hidden markov model. Evaluation of abnormality can be done using forward algorithm by comparing learned sequence and input sequence. Results of experiments show that modeling of semantic region is robust against noise in various scene.

Learning System of Programming Language using Basic Algorithms (기초 알고리즘을 활용한 프로그래밍 언어 학습 시스템)

  • Park, Kyoung-Wook;Oh, Kyeong-Sug;Ryu, Nam-Hoon;Lee, Hye-Mi;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.1
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    • pp.66-73
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    • 2010
  • The curriculum of programming education including algorithm has been recognized as a very important subject to many students majoring in natural sciences and engineering including electronic engineering and computer related departments. However, many students have had difficulties with it due to its characteristics; as a consequence, they have been in trouble taking upper-level subjects. Flow chart is a diagram that expresses logical stages necessary to solve certain problems and has been widely used to have an understanding of the flow of algorithm. The practice-oriented education of algorithm and programming would be very important to assist the understanding of operation processes. Furthermore, it has been desperately required to the necessity of auxiliary programs that could enhance an understanding of the concept of algorithm and program execution process. This study was aimed to design and embody the learning system of programming languages using basic algorithms so as for students to easily learn basic algorithm among the entire programming curriculum.

Applying the Fuzzy Decision-Making Method for Program Evaluation and Management Policy of Vietnamese Higher Education

  • TONG, Kiet Hao;NGUYEN, Quyen Le Hoang Thuy To;NGUYEN, Tuyen Thi Mong;NGUYEN, Phong Thanh;VU, Ngoc Bich
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.9
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    • pp.719-726
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    • 2020
  • Education policy is a dynamic process featuring social development trends. The world countries have focused their education program on empowering the learners for future life and work. This paper aims to assess the higher education curriculum based on a survey of 280 students, employers, alumni, and lecturers in both social sciences and natural sciences in Ho Chi Minh City, Vietnam. The fuzzy decision-making method, namely the Fuzzy Extent Analysis Method (F-EAM), was applied to measure the relative weight of each parameter. Seven factors under the curriculum development have been put in the ranking. Input with emphasis on foreign language was the highest priority in curriculum development, given the expected demand of the labor market. Objective and learning outcome and teaching activities ranked second and third, respectively. The traditional triangle of teaching content, methodology, and evaluation and assessment are still proven their roles, but certain modifications have been defined in the advanced curriculum. Teaching facilities had the least weight among the seven dimensions of curriculum development. The findings are helpful for education managers to efficiently allocate scarce resources to reform the curriculum to bridge the undergraduate quality gap between labor supply and demand, meeting the dynamic trends of social development.

Linking Korean Predicates to Knowledge Base Properties (한국어 서술어와 지식베이스 프로퍼티 연결)

  • Won, Yousung;Woo, Jongseong;Kim, Jiseong;Hahm, YoungGyun;Choi, Key-Sun
    • Journal of KIISE
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    • v.42 no.12
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    • pp.1568-1574
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    • 2015
  • Relation extraction plays a role in for the process of transforming a sentence into a form of knowledge base. In this paper, we focus on predicates in a sentence and aim to identify the relevant knowledge base properties required to elucidate the relationship between entities, which enables a computer to understand the meaning of a sentence more clearly. Distant Supervision is a well-known approach for relation extraction, and it performs lexicalization tasks for knowledge base properties by generating a large amount of labeled data automatically. In other words, the predicate in a sentence will be linked or mapped to the possible properties which are defined by some ontologies in the knowledge base. This lexical and ontological linking of information provides us with a way of generating structured information and a basis for enrichment of the knowledge base.

A Leveling and Similarity Measure using Extended AHP of Fuzzy Term in Information System (정보시스템에서 퍼지용어의 확장된 AHP를 사용한 레벨화와 유사성 측정)

  • Ryu, Kyung-Hyun;Chung, Hwan-Mook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.2
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    • pp.212-217
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    • 2009
  • There are rule-based learning method and statistic based learning method and so on which represent learning method for hierarchy relation between domain term. In this paper, we propose to leveling and similarity measure using the extended AHP of fuzzy term in Information system. In the proposed method, we extract fuzzy term in document and categorize ontology structure about it and level priority of fuzzy term using the extended AHP for specificity of fuzzy term. the extended AHP integrates multiple decision-maker for weighted value and relative importance of fuzzy term. and compute semantic similarity of fuzzy term using min operation of fuzzy set, dice's coefficient and Min+dice's coefficient method. and determine final alternative fuzzy term. after that compare with three similarity measure. we can see the fact that the proposed method is more definite than classification performance of the conventional methods and will apply in Natural language processing field.

A Semantic Similarity Measure for Retrieving Software Components (소프트웨어 부품의 검색을 위한 의미 유사도 측정)

  • Kim, Tae-Hee;Kang, Moon-Seol
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.6
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    • pp.1443-1452
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    • 1996
  • In this paper, we propose a semantic similarity measure for reusable software components, which aims to provide the automatic classification process of reusable to be stored in the structure of a software library, and to provide an efficient retrieval method of the software components satisfying the user's requirements. We have identified the facets to represent component characteristics by extracting information from the component descriptions written in a natural language, composed the software component identifiers from the automatically extracted terms corresponding to each facets, and stored them which the components in the nearest locations according to the semantic similarity of the classified components. In order to retrieve components satisfying user's requirements, we measured a semantic similarity between the queries and the stored components in the software library. As a result of using the semantic similarity to retrieve reusable components, we could not only retrieve the set of components satisfying user's queries. but also reduce the retrieval time of components of user's request. And we further improve the overall retrieval efficiency by assigning relevance ranking to the retrieved components according to the degree of query satisfaction.

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