• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.476-482
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• 2004

Question-Answering (QA) system has to analyze user's intention correctly to respond correct answer for user's question., This paper proposes a focus-word-based question analysis approach for Korean QA system to analyze user's intention correctly. focus-word is a clue-word which selects question type. The question type is determined to one in 75 subcategories using semantics of focus-words. the proposed system accomplished 97.18% accuracy for the main category and 95.31% accuracy for the subcategory in the question classification.

• Journal of Sasang Constitutional Medicine
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• v.18 no.1
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• pp.91-106
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• 2006

1. Objectives The purpose of this study is to find out the characteristics about the Sasang constitution of elementary school students based on the questions that have significant differences. 2. Methods 146 children who have visited Kang-Nam Kyung-Hee Oriental Hospital Sasang constitution center from Mar. 2003 to May. 2005, were investigated through the questionnaires. These have the categories of personality and emotional characteristics, personal relationship, playing and the way to handle things such as jobs or missions, behavioral characteristics, and etc., were analyzed statistically. 3. Results and Conclusions (1) In the category of the 'Personality and Emotional characteristics', significantly more Soeumin showed positive answers to the question, 'being easily nervous and get irritated' than the other groups, and significantly more Taeumin to the question, 'considerate and thoughtful' than Soyangin. (2) In the category of the 'Personal relationship', there were significantly more Soyangin who showed positive answer to the question 'making a friend easily' than the other groups. (3) In the category of the 'playing and the way to handle things', significantly more Soeumin showed positive answer to the question, 'love to do the exercise' than Soyangin, and significantly more Soeumin showed positive answer to the question, 'not careful and meticulous' than Soyangin, and significantly more Soeumin showed positive answer to the question, 'like to read books' than Taeumin. (4) In the category of the 'Behavioral characteristics', significantly more Soyangin showed positive answer to the question, 'unable to concentrate just one thing even for just a minute and keep on moving.' than the other groups, and significantly more Soyangin showed positive answer to the question, 'act or response quick.' than Taeumin, and significantly more Soyangin showed positive answer to the question, 'behave and go around restlessly and flighty' than Soeumin, and significantly more Taeumin showed the positive answer to the question, 'hate to move by oneself' than Soyangin.

• Journal of Korean Library and Information Science Society
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• v.36 no.4
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• pp.329-347
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• 2005

Collaborative Digital Reference Service( CDRS) has spread worldwide as a tool of obtaining high-quality information in knowledge information society KISTI formed CDRS collaboration model called Question포인트+ with 4 institutions in Korea. In Question포인트+ which is also linked to the Global Network, the domestic and oversea information specialists answer a variety of questions in response of the requests of users on the web. The implementation of Question포인트+ is significant as the first domestic CDRS collaboration model, and contribute to management, dissemination, and activation of CDRS in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.27-36
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• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• Journal of Science Education
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• v.39 no.1
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• pp.58-79
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• 2015

This study is to analyze the 2289 students questionnaires from 3rd to 9th grade students in order to analyze the students' perceptions change aspect by their grade about the frequency and type of students' question during various science class context. After the class contexts proposed in the questionnaire subcategorize into 19 subitems about 4 areas of class content, class pattern, class material and class process, this study examined the frequency and type of students' question during a science class by each item. The results of this study were as follows. First, the type of students' question was that the most frequent was understanding question and the second was memory question and these both types were half frequency. There was no special tendency related the change of students' question type by school year. Second, the frequency of 4th grade students' question was the highest among other school year students and the frequency of students' question was lowered by the higher school year. The change of students' question by school year was the biggest between 3rd and 4th grade. The class strategies for improving the class effect reflect that the various and active students' question by class context and school year stimulates students' thinking and also builds up the active class environment.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.20-31
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• 2006

This study analysed student teachers' notable questions about the earth science contents in the elementary science textbooks. The contents of notable questions were defined as ‘notable question contents 1' and 'notable question contents 2'. Both the question contorts are contents about which the number of questions is above three times and from two times to three times as much as the mean number of questions per page of each unit respectively. The results are as follows. First, question contents 1 are found as 'clouds observation', 'geological strata formation' and so on. Question contents 2, 'rainfall measurement', 'moon's movement during one night' and so on are found. Second, the number of interrelationships of main terms in questions increased in each question of question contents 1, but 4 term-patterns are found more in question contents 2 than question contents 1. Third, high interrelationship patterns of terms in question contents 1 are 'coal and petroleum-generation', 'metamorphosis-heat and pressure', 'metamorphosis-heat and pressure-metamorphic rocks', 'planet-sun-comet-revolution' and in question contents 2. 'constellation plate-use', 'dryness and wetness hygrometer-principle', 'seismograph-principle-earthquake', 'earth rotation axis-tilting-occurrence', 'dryness and wetness hygrometer-principle-humidity' and so on. The sources of questions analysed in this study are estimated as the content construction system of textbooks, or students' general questions about the earth science contents. If this is the former, the problems in texts and illustrations in textbooks should be articulated and resolved. And if the latter, the elementary science curriculum has to be reconsidered in view of scientific literacy in earth science.

• ETRI Journal
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• v.42 no.6
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• pp.899-911
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• 2020

The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

• Korean Journal of Logic
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• v.19 no.2
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• pp.185-232
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• 2016

In order to explain why begging the question is a fallacy, some of the challenges must be met. First we need to understand what begging the question is in subtle ways. In addition, it is necessary to reflect on the nature and the purpose of arguments in order to explain why begging the question is a fallacy. In this paper, I first have a general proposal about the main purpose of arguments. Then I place my own multi-layered theory of begging the question proposed in a previous study in the context of the proposals in this paper for the main purpose of arguments. Moreover, I develop a more comprehensive theory of why begging the question is a fallacy. Finally, I examine and criticize the main previous theories of begging the question, such as Frank Jackson's theory, Douglas Walton's theory, David Sanford's theory, John Biro's theory.

• Journal of the Korean Society for information Management
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• v.32 no.3
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• pp.397-412
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• 2015

The main goal of this study is to investigate how to route a question to some relevant users who have interest in the topic of the question based on users' topic interest. In order to assess users' topic interest, archived question-answer pairs in the community were used to identify latent topics in the chosen categories using LDA. Then, these topic models were used to identify users' topic interest. Furthermore, the topics of newly submitted questions were analyzed using the topic models in order to recommend relevant answerers to the question. This study introduces the process of topic modeling to investigate relevant users based on their topic interest.