• Communications of the Korean Mathematical Society
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• v.37 no.1
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• pp.65-74
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• 2022

A valued field (K, ν) is called defectless if each of its finite extensions is defectless. In [1], Aghigh and Khanduja posed a question on defectless extensions of henselian valued fields: "if every simple algebraic extension of a henselian valued field (K, ν) is defectless, then is it true that (K, ν) is defectless?" They gave an example to show that the answer is "no" in general. This paper explores when the answer to the mentioned question is affirmative. More precisely, for a henselian valued field (K, ν) such that each of its simple algebraic extensions is defectless, we investigate additional conditions under which (K, ν) is defectless.

• English Language & Literature Teaching
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• v.17 no.4
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• pp.123-139
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• 2011

The purpose of the current study is to analyze a model of OPIc-based speaking test for Korea English classroom. The research questions were (1). What is the English teachers' opinion on the current speaking teaching and testing? (2). Is the OPIc speaking test appropriate in the Korea English class? and (3). What are the English education students' perceptions of the OPIc-based speaking test for English classes? To answer the first research question, a survey was conducted targeting one hundred and forty-seven teachers. The result of the survey shows that Korea English teachers' great concern on the English teaching and speaking test are "communicative competence," "scoring and criteria," and "condition and need." To answer the second research question, the OPIc speaking test for the class was analyzed and it was found that in terms of the communicative competence," "scoring and criteria," and "condition and need" issues, OPIc based speaking test is appropriate in Korea English class. For the third research question, Q methodology was used targeting English education students and the result shows that most English education students strongly agree to the statements that the OPIc-based speaking test has the advantage to improve communicative competence. This study may provide the information about creating and adopting tests for English classes and relating standardized test and the English classes.

• Language and Information
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• v.10 no.2
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• pp.21-45
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• 2006

Connectivity effects have been central issues in dealing with specificational pseudoclefts. While syntactic approaches motivate their analysis in order to explain connectivity effects in terms of a connected clause, these accounts have numerous problems including a wide range of anti-connectivity effects that constitute crucial counterevidence. On the other hand, semantic accounts of connectivity effects treat BV and BT connectivity by independent interpretive mechanisms providing a more fundamental explanation for connectivity effects. Yet existing semantic accounts have limitations in explaining syntactic properties and syntactic connectivity effects in SPCs, and in accounting for BV anti-connectivity effects in English. Focusing on BV connectivity, this paper explores how the relevant (anti-)connectivity facts can be accounted for by an analysis that provides both an elaborate syntactic analysis of SPCs and a semantic mechanism for bound anaphora. Based on Yoo's (2005) non-deletion based, question-answer pair analysis of SPCs, this paper shows that a functional question analysis of a specificational subject, when combined with a theory of operator scope and a non-configurational condition on bound anaphora, can explain various BV (anti-)connectivity patterns in SPCs and related constructions.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.577-584
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• 2015

In general, Q&A system retrieves passages by matching terms of a question in order to find an answer to the question. However it is difficult for Q&A system to find a correct answer because too many passages are retrieved and matching using terms is not enough to rank them according to their relevancy to a question. To alleviate this problem, we introduce a topic for a sentence, and adopt it for ranking in Q&A system. We define a set of person-related topic class and a clue expression which can indicate a topic of a sentence. A topic classification system proposed in this paper can determine a target topic for an input sentence by using clue expressions, which are manually collected from a corpus. We explain an architecture of the topic classification system and evaluate the performance of the components of this system.

• International Journal of Contents
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• v.1 no.2
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• pp.39-43
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• 2005

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.478-480
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• 2002

질의 응답 시스템의 성능을 높이기 위해서는 정답 후보(Answer Candidate)를 랭킹하는 방법이 매우 중요하다. 본 논문에서는 기존의 정답 후보 랭킹을 위해 사용하던 위치 근접성의 문제점을 제시하고, 이를 보완하기 위한 구문 근접성을 이용하는 방법에 대해 제안한다. 실험 결과는 논문에서 제안한 구문 근접성을 사용한 정답 후보 랭킹 방법이 위치 근접성을 이용만 방법보다 더 개선된 방법임을 보여준다

• The Journal of Korean Association of Computer Education
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• v.11 no.1
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• pp.65-74
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• 2008

In this paper, we introduce an analysis system for answer dataset by using a data mining method. We analyze students' answer data collected from a test including multiple choice question items, and find associations between the items. Analysis of evaluation results based on our system will not only provide correct information on students' achievement levels but also provides a basis for modifying weaknesses of the evaluation procedures, question items, or teaching/learning procedures. Furthermore, it will enable us to improve the quality of question items for future use so that we can secure itemsets of high quality.

• Journal of Korean Elementary Science Education
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• v.30 no.4
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• pp.468-481
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• 2011

This research is to observe and analyze the student interactions when inquiry problems were generated along with the students by using asynchronous discussion methods with the class bulletin board. For this research, 10 students from a single class of 6th grade were selected. The subject students were divided into 2 groups by cognitive levels. After the students were submitted the 4 problem situations for 1 week each, the discussion process was analyzed. The research results are as follows. First, the analysis of the step by step interactive discussion showed that several students answered for the question from a single student while discussing first for the question and answer in a form of a question with many multiple answers without any connections with the previously asked questions. At the end of the discussion, one to two students answered to a question by taking turns and the type of discussion changed to one question - one answer type by answering to the person who spoke prior to the next. Second, the discussion took place with the students in the transitional stage speaking in time in order, to provide comments to the bottom of the linear form and students in the formal operational stage students speaking in temporal order, regardless of the number of comments in the direction of the radiation(mind map) forms. The individual comment speaking rates were similar in the two groups so the students were able to speak indiscriminately.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.529-536
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• 2004

The main idea of this paper is to combine position information in sentence and query type classification to make the documents ranking to query more accessible. First, the use of conceptual graphs for the representation of document contents In information retrieval is discussed. The method is based on well-known strategies of text comparison, such as Dice Coefficient, with position-based weighted term. Second, we introduce a method for learning query type classification that improves the ability to retrieve answers to questions from Question Answering system. Proposed methods employ naive bayes classification in machine learning fields. And, we used a collection of approximately 30,000 question-answer pairs for training, obtained from Frequently Asked Question(FAQ) files on various subjects. The evaluation on a set of queries from international TREC-9 question answering track shows that the method with machine learning outperforms the underline other systems in TREC-9 (0.29 for mean reciprocal rank and 55.1% for precision).

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.