• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.125-134
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• 2008

We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.253-263
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• 2017

As needs for knowledge on Korean history and the attention of the people are rapidly increasing, various smartphone applications for learning the history have appeared during recent years. These applications provide multiple choice questions to users through their own problem banks. But, since these questions are selected from the fixed set of problems that are stored previously, the learning efficiency of users is inevitably decreased when they use the applications repeatedly. In this paper, we present a question generation system named K-History which generates multiple choice questions in an automatic way using the database on the history of Korea. In addition, we also describe the development of the application Korean History Infinite Challenge as a learning application for Korean history. To develop K-History, we classify typical types of learning problems through various problems based on Korean history learning materials, proposing algorithms to generate problems according to the types found. Through the developed techniques, various learning systems can reduce the cost for creating questions, while increasing the learning efficiency of users.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.339-346
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• 2017

There is increasing interest in text analysis based on unstructured data such as articles and comments, questions and answers. This is because they can be used to identify, evaluate, predict, and recommend features from unstructured text data, which is the opinion of people. The same holds true for TEL, where the MOOC service has evolved to automate debating, questioning and answering services based on the teaching-learning support system in order to generate question topics and to automatically classify the topics relevant to new questions based on question and answer data accumulated in the system. Therefore, in this study, we propose topic modeling using LDA to automatically classify new query topics. The proposed method enables the generation of a dictionary of question topics and the automatic classification of topics relevant to new questions. Experimentation showed high automatic classification of over 0.7 in some queries. The more new queries were included in the various topics, the better the automatic classification results.

• Journal of The Korean Association of Information Education
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• v.20 no.2
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• pp.197-206
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• 2016

A fill-in-the-blank with choices are widely used in classrooms in order to check whether students' understand what is being taught. Although there have been proposed many algorithms for generating this type of questions, most of them focus on preparing sentences with blanks rather than generating multiple choices. In this paper, we propose a novel algorithm for generating multiple choices, given a sentence with a blank. Because the algorithm is based on a statistical language model, we can generate relatively unbiased result and adjust the level of difficulty with ease. The experimental results show that our approach automatically produces similar multiple-choices to those of the exam writers.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2431-2441
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• 1999

Equations are widely used in representing information. One of the basic questions about equations is to determine whether a given equation follows logically from the set of equations. Rewrite systems are one of the method to answer many instances of this problem. A rewrite system simplifies a given term by applying rewrite rules successively. Hence it is important that the process of simplification does not go on indefinitely. One of the methods to check whether a rewrite system terminates (that is, the rewrite system does not go on indefinitely) is polynomial orderings. A polynomial ordering assigns an appropriate polynomial to each function symbol. However, how to assign polynomials to function symbols is not known. We propose an automatic way of generating polynomial orderings using genetic algorithms.

• Geomechanics and Engineering
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• v.31 no.5
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• pp.439-452
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• 2022

A forecast of slope behavior during catastrophic events, such as earthquakes is crucial to recognize the risk of slope failure. This paper endeavors to eliminate the significant supposition of predefined slip surfaces in the slope stability analysis, which questions the relevance of simple conventional methods under seismic conditions. To overcome such limitations, a methodology dependent on the slip line hypothesis, which permits an automatic generation of slip surfaces, is embraced to trace the extreme slope face under static and seismic conditions. The effect of earthquakes is considered using the pseudo-static approach. The current outcomes developed from a parametric study endorse a non-linear slope surface as the extreme profile, which is in accordance with the geomorphological aspect of slopes. The proposed methodology is compared with the finite element limit analysis to ensure credibility. Through the design charts obtained from the current investigation, the stability of slopes can be assessed under seismic conditions. It can be observed that the extreme slope profile demands a flat configuration to endure the condition of the limiting equilibrium at a higher level of seismicity. However, a concurrent enhancement in the shear strength of the slope medium suppresses this tendency by offering greater resistance to the seismic inertial forces induced in the medium. Unlike the traditional linear slopes, the extreme slope profiles mostly exhibit a steeper layout over a significant part of the slope height, thus ensuring a more optimized solution to the slope stability problem. Further, the susceptibility of the Longnan slope failure in the Huining-Wudu seismic belt is predicted using the current plasticity approach, which is found to be in close agreement with a case study reported in the literature. Finally, the concept of equivalent single or multi-tiered planar slopes is explored through an example problem, which exhibits the appropriateness of the proposed non-linear slope geometry under actual field conditions.

• CRM연구
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• v.2 no.2
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• pp.53-70
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• 2009

Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.