• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.138-144
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• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• Journal of Korean Elementary Science Education
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• v.38 no.1
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• pp.130-148
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• 2019

This study compared the characteristics of scientific poems written by scientifically-gifted and general elementary students, and their perceptions of writing scientific poem. To do this, 5~6 graders (n=100) at two gifted science education institutes and 5~6 graders (n=93) at a elementary school in Seoul were selected. Scientific poems written by the students were analyzed according to their numbers and types. Their perceptions of writing scientific poems were also analyzed through a questionnaire and group interviews. The analysis of the results revealed that the general students wrote more scientific poems than the scientifically-gifted students for thirty minutes. The general students mainly named the titles in a direct way, while scientifically-gifted students did it in an implicit way. The free verse poems in both general students and scientifically-gifted students appeared most frequently, and the prose or narrative poems also often appeared. The general and scientifically-gifted students frequently used impersonation, and some students did not use metaphors. They didn't connect the scientific knowledge for multiple grade. While the poems of the general students evenly included the scientific knowledge for various academic fields, those of scientifically-gifted students tended to include the scientific knowledge for physics or chemistry. The poems of scientifically-gifted students tended to include more science process skills, especially in basic inquiry skills, than those of general students. The scientifically-gifted students wrote scientific poems in a more expanded form regarding the scientific knowledge, than the general students. Scientifically-gifted students perceived the educational benefits of writing scientific poems more positively based on various cognitive and affective aspects. However, many scientifically-gifted and general students had also several difficulties in the processes of writing scientific poems. Educational implications of these findings are discussed.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.1010-1017
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• 1999

불완전한 계획 영역 이론은 오류 영역(noisy domain)에서 하나의 상태에 상반된 연산자들이 적용되는 불일치성 문제를 야기할 수 있다. 이 문제를 해결하기 위해서 본 논문은 상태를 기술하기 위해 다치 논리를 도입하여 제어지식으로서의 부정적 선행조건을 학습하는 새로운 방법을 제안한다. 기계에는 알려지지 않은 이러한 제어지식이 인간에게는 반대개념으로 잠재적으로 사용되고 있다. 이러한 잠재된 개념을 학습하기 위해 본 논문은 반대 연산자들로 구성된 사이클을 영역이론으로부터 기계적으로 생성하고, 이 연산자들에 대한 실험을 통해 반대 리터럴(literal)들을 추출한다. 학습된 규칙은 불일치성을 방지하면서 동시에 중복된 선행조건을 제거하여 연산자를 단순화시킬 수 있다.Abstract An incomplete planning domain theory can cause an inconsistency problem in a noisy domain, allowing two opposite operators to be applied to a state. To solve the problem, we present a novel method to learn a negative precondition as control knowledge by introducing a three-valued logic for state description. However, even though the control knowledge is unknown to a machine, it is implicitly known as opposite concept to a human. To learn the implicit concept, we mechanically generate a cycle composed of opposite operators from a domain theory and extract opposite literals through experimenting the operators. A learned rule can simplify the operator by removing a redundant precondition while preventing inconsistency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.147-152
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• 2016

One of major issues in machine learning that extracts and acquires knowledge implicit in data is to find an appropriate way of representing it. Knowledge can be represented by a number of structures such as networks, trees, lists, and rules. The differences among these exist not only in their structures but also in effectiveness of the models for their problem solving capability. In this paper, we propose partition utility as a criterion function for clustering that can lead to simplification of the model and thus avoid overfitting problem. In addition, a heuristic is proposed as a way to construct balanced hierarchical models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.53-62
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• 2008

Cross-lingual text retrieval(CLTR) is the information retrieval in which a user tries to search a set of documents written in one language for a query another language. This thesis proposes a CLTR system based on fuzzy multilingual thesaurus to handle a partial matching between terms of two different languages. The proposed CLTR system uses a fuzzy term matrix defined in our thesis to perform the information retrieval effectively. In the defined fuzzy term matrix, all relation degrees between terms are inferred from using the transitive closure algorithm to reflect all implicit links between terms into processing of the information retrieval. With this framework, the CLTR system proposed in our thesis enhances the retrieval effectiveness because it is able to emulate a human expert's decision making well in CLTR.

• Asia Pacific Journal of Corpus Research
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• v.2 no.2
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• pp.17-29
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• 2021

The current study explores small corpora of critiques written by Chinese and non-Chinese university students and how strategies used by these writers compare with high-rated L1 students. Data collection includes three small corpora of student writing; 20 student critiques in 2017, 23 student critiques from 2018, and 23 critiques from the online Michigan MICUSP collection at the University of Michigan. The researchers employ Text Inspector and Lexical Complexity to identify university students' vocabulary knowledge and awareness of syntactic complexity. In addition, WMatrix4® is used to identify and support the comparison of lexical and semantic differences among the three corpora. The findings indicate that gaps between Chinese and non-Chinese writers in the same university classes exist in students' knowledge of grammatical features and interactional metadiscourse. In addition, critiques by Chinese writers are more likely to produce shorter clauses and sentences. In addition, the mean value of complex nominal and coordinate phrases is smaller for Chinese students than for non-Chinese and MICUSP writers. Finally, in terms of lexical bundles, Chinese student writers prefer clausal bundles instead of phrasal bundles, which, according to previous studies, are more often found in texts of skilled writers. The current study's findings suggest incorporating implicit and explicit instruction through the implementation of corpora in language classrooms to advance skills and strategies of all, but particularly of Chinese writers of English.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.89-101
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• 1999

Increasing number of companies recognize that the understanding of customers and their markets is indispensable for their survival and business success. The companies are rapidly increasing the amount of investments to develop customer databases which is the basis for the database marketing activities. Database marketing is closely related to data mining. Data mining is the non-trivial extraction of implicit, previously unknown and potentially useful knowledge or patterns from large data. Data mining applied to database marketing can make a great contribution to reinforce the company's competitiveness and sustainable competitive advantages. This paper develops the classification model to select the most responsible customers from the customer databases for telemarketing system and evaluates the performance of the developed model using LIFT measure. The model employs the decision tree algorithm, i.e., CHAID which is one of the well-known data mining techniques. This paper also represents the effective database marketing strategy by applying the data mining technique to a credit card company's telemarketing system.

• IE interfaces
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• v.1 no.1
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• pp.85-99
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• 1988

High Touch product is characterized by shorter life cycle together with specification/integration of existing function in order to capitalize the rapidly emerging high technology. R & D strategy for a development of High Touch product generally emphasizes two aspects ; Industrial Design (ID) and Ergonomic Design (ED). However, working knowledge on ED of a systematic identification of potential High Touch products is not readily available. The purpose of this study was three-folded : (1) To emphasize the fact that greater efforts should be geared to ED in High Touch design ; (2) To develop an ergonomic approach based on analysis of implicit human needs that identifies potential area of High Touch ; (3) To bubble with new and probable High Touch products in home electronics that actually demonstrate the validity of this study.

• Journal of Korean Academy of Nursing
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• v.24 no.4
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• pp.616-622
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• 1994

Precise concept analysis has been neglected be-cause of a lack of understanding of its necessity and a lack of conceptual analytic knowledge. Concept analysis is the mental work of examining parts, phenomenon and the interrelated whole of a thing. Focus in this article is to extract the critical attributes of hardiness and make an operational delinition. The process of concept analysis is illustrated and documented using the analytic approach described by Walker and Avant (1983). To explore the explicit or implicit meanings of hardiness, existing literature was reviewed. The evolution of hardiness and the dictionary definitions were also added. Hardiness can be defined as follows : A condition of being inured to fatigue or hardship which has three subcomponents-challenge, control and commitment. Critical attributes of hardiness were extracted that may be used in naming the occurrence of the phenomenon. Model case, contrary case, borderline case and related case were described. Antecedents and consequences were explored. The defining critical attributes of hardiness are : 1. Resistance-hardiness involves resistance of stress or hardship. 2. Hardiness involves appraisal of change as a chance. 3. Hardiness implies interpretation of events and self as influential,. 4. Hardiness requires active involving reaction Implications for nursing and for further study are added.

• The Journal of Information Technology
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• v.9 no.3
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• pp.27-32
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• 2006

If is interested and create rule between it in item that association rules buys, by negative association rules is interested to item that do not buy, it is attempt to do data Maining more effectively. It is difficult that existent methods to find negative association rules find one part of rule, or negative association rules because use more complicated algorithm than algorithm that find association rules. Therefore, this paper presents method to create negative association rules by simpler process using Boolean Analyzer that use dependency between items. And as Boolean Analyzer through an experiment, show that can find negative association rules and more various rule through comparison with other algorithm.