• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.448-451
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• 2005

In this paper, we describe a method of answer extraction on a concept-based question-answering system. The concept-based question answering system is a system which extract answer using concept information. we have researched the method of answer extraction using concepts which analyzed and extracted through question analysing with answer extracting rules. We analyzed documents including answers and then composed answer extracting rules. Rules consist of concept and syntactic information, we generated candidates of answer through the rules and then chose answer.

• International Journal of Contents
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• v.2 no.1
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• pp.17-21
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• 2006

In this paper, we describe a concept-based question-answering system in which concept rather than keyword itself makes an important role on both question analysis and answer extraction. Our idea is that concepts occurred in same type of questions are similar, and if a question is analyzed according to those concepts then we can extract more accurate answer because we know the semantic role of each word or phrase in question. Concept frame is defined for each type of question, and it is composed of important concepts in that question type. Currently the number of question type is 79 including 34 types for person, 14 types for location, and so on. We experiment this concept-based approach about questions which require person s name as their answer. Experimental results show that our system has high accuracy in answer extraction. Also, this concept-based approach can be used in combination with conventional approaches.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.1-10
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• 2005

This paper presents the information retrieval system which can retrieve the most appropriate answer sentence for user queries by using the concept and the attribute for the knowledge retrieval. The system analyzes the user query into the Boolean queries with the concept and the attribute and then retrieve the relevant documents in the indexing set of answer documents. Users can retrieve the relevant answer sentences from the relevant documents. For this, the answer documents indexed by the concept and the attribute are segmented by each sentence respectively. Thus, the segmented sentences are analyzed into the concept and the attribute of which the relevance degree with indexing units of documents is evaluated. Then, the system indexes the location of answer sentences. In the experiment, we evaluate the performance of our answer retrieval system against 100 user queries and show the experimental results.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.10-20
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• 2007

This paper describes a concept-based question analysis to analyze concept which is more important than keyword for the accurate answer extraction. Our idea is that we can extract correct answers from various paragraphs with different structures when we use well-defined concepts because concepts occurred in questions of same answer type are similar. That is, we will analyze the syntactic and semantic role of each word or phrase in a question in order to extract more relevant documents and more accurate answer in them. For each answer type, we define a concept frame which is composed of concepts commonly occurred in that type of questions and analyze user's question by filling a concept frame with a word or phrase. Empirical results show that our concept-based question analysis can extract more accurate answer than any other conventional approach. Also, concept-based approach has additional merits that it is language universal model, and can be combined with arbitrary conventional approaches.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.419-430
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• 2009

Reading comprehension (RC) systems are to understand a given text and return answers in response to questions about the text. Many previous studies extract sentences that are the most similar to questions as answers. However, texts for RC tests are generally short and facts about an event or entity are often expressed in multiple sentences. The answers for some questions might be indirectly presented in the sentences having few overlapping words with the questions. This paper proposes a conceptual graph matching method towards RC tests to extract answer strings. The method first represents the text and questions as conceptual graphs, and then extracts subgraphs for every candidate answer concept from the text graph. All candidate answer concepts will be scored and ranked according to the matching similarity between their sub-graphs and question graph. The top one will be returned as answer seed to form a concise answer string. Since the sub-graphs for candidate answer concepts are not restricted to only covering a single sentence, our approach improved the performance of answer extraction on the Remedia test data.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.2
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• pp.42-48
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• 2017

OCD (Operational Concept Document) is very important in system development. To develop OCD we should answer questions about, what template to use, what is the overall process to develop OCD, what kinds of diagrams we should use and how can we validate the OCD. To answer about the template we compared tow industrial guide on operational concept development and tailored it. For development process, we proposed a comprehensive process which satisfies the requirements of the project context. For use of proper diagram, we analyzed many kinds of diagrams used in representing behavior of system and choose some diagrams which best fit for our purpose. Finally we established validation criteria for operational scenario and requirement texts in operational concept documents.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.457-463
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• 2015

This paper presents the need for the concept of collective intelligence based system for the timely learning and incorrect notes show the utilization and satisfaction. The old wrong answer note system is characterized by the provision of uniform right answer explanations for the questions whose answers were wrong by checking whether the evaluation items were answered right or wrong. The characteristic requires a lot of improvements in terms of wrong answer analysis and feedback since it cannot properly receive feedback on the items that a learner got right by luck in spite of poor understanding of them and on the errors in the selection process of wrong answers by individual learners. The SERO wrong answer note was designed to propose new ways to identify and capture such "score errors" and compensate for the practical weaknesses of learners. The Stability Emergency Risk Opportunity (SERO) wrong answer note is based on a method of categorizing and analyzing evaluation items answered by the examinee into four types (S, E, R and O type), and commentary correct as well as incorrect answers by presenting a variety of commentary notes using the collective intelligence of the study show that satisfaction is high.

• Journal of Korean Clinical Health Science
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• v.4 no.4
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• pp.730-736
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• 2016

Purpose. The aim of this study was to provide Aromatherapist with analysis of the effect of natural aroma essential oil on middle school students' self-concept. Methods. In total, 20 students were recruited to answer a self-administered questionnaire in pre and post. The questionnaire was composed of questions about general self-concept, class self-concept, achievement self-concept, ability self-concept, social self-concept, family self-concept, emotional self-concept, physical self-concept. The natural aroma essential oil program was operational in a 90-minute once a week for ten weeks. Results. As a result, the score of emotional self-concept(t=-2.60, p<.05) is higher than pre the experiment post experiment. Conclusions. This study is to get a basic data of natural aroma should be applied to improve self-concept of middle school students.

• Korean Journal of Mathematics
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• v.25 no.1
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• pp.61-70
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• 2017

In this paper, we introduce the concept of statistically sequentially quotient map which is a generalization of sequence covering map and discuss the relation with covering maps by some examples. Using this concept, we give an affirmative answer for a question by Fucai Lin and Shou Lin.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.86-91
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support their decision making. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studiedmoretohelpmanagersmakerightdecisions.