• 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.

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.271-286
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• 2006

In this paper, we introduce automatic question generation technique using the language resources like User-Word Intelligent Network(U-WIN) and Korean dictionary including quite a for of information. And we present Korean word learning system with this technique. The item pool method which almost learning-system are using makes some problems. As a solution of the problems, we classified into 8 question type and implemented the Korean word learning system which is making the Korean question automatically by using the morphological and semantic information according to the automatic question generation pattern of each type.

• Communications of Mathematical Education
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• v.36 no.4
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• pp.487-509
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• 2022

The purpose of this study is to analyze classroom discourse in the math classroom of middle school in China, which has a unique math classroom background of entrance examination for high school. To this end, this study analyzed teacher question statistics and episodes by teacher question type as starting speech in mathematics classroom discourse, and five IRF subtypes were especially identified by class discourse structure analysis. The data were analyzed focusing on a total of 15 transcripts of math classes recorded by three math teachers at H School in Guiyang, Guizhou Province, China, and written interviews of teachers. According to the results of this study, an average of 20 teacher questions were observed for each class, and the teacher question type was classified into confirmation question (understanding confirmation question, explanation request question, and double check question) and information question (information presentation question). In addition, according to classroom discourse analysis, the IRF discourse structure was divided into fragmentary evaluation, evaluation+reason, evidence of explanation, evaluation+student response re-statement, guidance on other thoughts or solutions, and student answer correction or teacher opinion presentation.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.401-417
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• 2015

Question taxonomy is one of main approaches to understand the questioner's information need so that we can assign relevant answerers to the question submitted by the user. The goal of this study is to investigate question taxonomy of question and answering services, which are available online and in libraries and understand the characteristics of question answering services by type. In order to achieve the goal, this study examines the types of questions appeared in literature, specifically focusing on social reference, question answering systems, and reference services, and then provides a summary of question taxonomy found in question answering services.

• Journal of Science Education
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• v.34 no.1
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• pp.105-112
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• 2010

The purpose of this research was to investigate relations between prior knowledge and primary grade science brilliant intellect's observation and inquiry. The subjects were selected 'Spider and cobweb' that self-regulation quest is available. Subjects were divided into two groups with one group having no prior knowledge about research subject. Compared observation method question type and level that appear between subject achievement to group. Target learning group are 5 ~ 6 school year 17 people for national university for the gifted center of local middle city. Researcher collected and analyzed data using summer vacation concentration education period. Source collection subject's research recording paper, subject's voice recording device, interview data etc. A data analysis tool took advantage of observation method that is studied in existing, question type, question level. Research was able to conclude : First, observation of prior knowledge happened than mass of students who many mass of students are few relatively vigorously. Second, primary grade science brilliant intellect students used more mainly manufacturing observation than simplicity observation that use senses regardless of relative quantity of prior knowledge. Third, prior knowledge expressed variety when many mass of students observe operation relatively.

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.297-303
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• 2005

When confronted with a query, question answering systems endeavor to extract the most exact answers possible by determining the answer type that fits with the key terms used in the query. However, the efficacy of such systems is limited by the fact that the terms used in a query may be in a syntactic form different to that of the same words in a document. In this paper, we present an efficient semantic query expansion methodology based on a question category concept list comprised of terms that are semantically close to terms used in a query. The semantically close terms of a term in a query may be hypernyms, synonyms, or terms in a different syntactic category. The proposed system constructs a concept list for each question type and then builds the concept list for each question category using a learning algorithm. In the question answering experiments on 42,654 Wall Street Journal documents of the TREC collection, the traditional system showed in 0.223 in MRR and the proposed system showed 0.50 superior to the traditional question answering system. The results of the present experiments suggest the promise of the proposed method.

• The Korean Journal of Health Service Management
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• v.7 no.3
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• pp.193-202
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• 2013

This study aimed to investigate and compare the perception of personal protective equipments and instrument sterilization of students who are in attendance at colleges and universities and which have bedside training as a regular subject in their curriculum for third-year students. 'Completely True' is the highest response to the question about the importance of wearing gloves, mask and medical gown from all groups. 'Completely True' is the highest response to the question about the necessity for replacement of gloves from all groups. 'Moderate True' is the highest response to the question about the necessity for replacement of mask from the group without practical training and 'Completely True' is the highest response to the question about the importance of hair cleanliness from all groups regardless of practical training experience. For the question about the perception of instrument disinfection and sterilization, the group with inside and outside practical training showed the highest perception level. Consequently, the right education for prevention of infection by setting inclusive guidelines to enhance the level of perception and practice seems continuously necessary.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.1-8
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• 2007

When confronted with a query, question answering systems endeavor to extract the most exact answers possible by determining the answer type that fits with the key terms used in the query. However, the efficacy of such systems is limited by the fact that the terms used in a query may be in a syntactic form different to that of the same words in a document. In this paper, we present an efficient semantic query expansion methodology based on query patterns in a question category concept list comprised of terms that are semantically close to terms used in a query. The proposed system first constructs a concept list for each question type and then builds the concept list for each question category using a learning algorithm. The results of the present experiments suggest the promise of the proposed method.

• ETRI Journal
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• v.41 no.6
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• pp.771-781
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• 2019

We propose the VS³-NET model to solve the task of question answering questions with machine-reading comprehension that searches for an appropriate answer in a given context. VS³-NET is a model that trains latent variables for each question using variational inferences based on a model of a simple recurrent unit-based sentences and self-matching networks. The types of questions vary, and the answers depend on the type of question. To perform efficient inference and learning, we introduce neural question-type models to approximate the prior and posterior distributions of the latent variables, and we use these approximated distributions to optimize a reparameterized variational lower bound. The context given in machine-reading comprehension usually comprises several sentences, leading to performance degradation caused by context length. Therefore, we model a hierarchical structure using sentence encoding, in which as the context becomes longer, the performance degrades. Experimental results show that the proposed VS³-NET model has an exact-match score of 76.8% and an F1 score of 84.5% on the SQuAD test set.

• Journal of Families and Better Life
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• v.9 no.2
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• pp.345-366
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• 1991

The concrete purpose of this study is to examine the possibility of applying S.Minuchin's structural family therapy theory to each clinical families so that it can solve efficiently the clinical problems Korean family. The test results are as follows: 1)The Results of Question I : Types of Korean family problems can be divide into six. Then the most frequent type of problem was marital problem. 2) The Results of Question II: Korean normal family showed rater difussed boundary and higher rate of wife dominant type than that of husband dominant type in aspect of boundary and power, and had low tendency toward alignment and neutral adjustment. 3)The Results of Quesion III; Amidst the clinical families, family structural traits of the families which have marital problems showed a clear boundary, the tendency toward alignment, and higher tate of husband dominant type than that of wife dominant type. And family structural traits of children problem family had the tendency of alignment and showed little wife-dominanted families in power. Finally, mother-in -law and daughter-in-law problemed family had several characters such as diffused boundary, the tendency of alignment and high adjustment. 4)The Results of Question IV : As a result of camparing problemed families with normal families in family structure, there was high adaptability of S.Minuchin's structural theory to the two family groups; the groups of marital problems and those of children problem.