• The Research Journal of the Costume Culture
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• v.13 no.2 s.55
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• pp.289-299
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• 2005

Through the formative analysis of the traditional jokakbo, we have composed surface composition that was made by a perfect square, triangle, a weather vane type, vertical type, cintamani type, and a mixed rectangular. And we have composed 18 kinds of motif stimulants that was made by vivid tone, pale tone, and so on, and finally analyzed sensibility image, preference rate of them. The cause of composition for the sensibility image of stimulant was composed by the cause of simplicity characteristics, interesting characteristics, rigid-flexibility characteristics, and modern characteristics. And from these things, the cause of simplicity characteristics and the cause of interesting characteristics were revealed as important dimensional factors of sensibility image. The sensibility image of motif was revealed as a simple image of perfect square, a feminine image of cintamani type, a modern image of mixed rectangular. And black-white colored mixed rectangular and chromatic colored cintamani type were also revealed as an interesting image. The preference rate of motif is related with the cause of interesting characteristics and simplicity characteristics, it also has been revealed to prefer the pale tone than others. And it also has been revealed that achromatic colored mixed rectangular, cintamani type of vivid tone, perfect square and rectangular of pale tone were mostly preferred.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1097-1104
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• 2011

In this paper, we propose a semantic web approach for personalized book recommendation. Our approach takes advantage of the content-based recommendation and improves its disadvantage that users should input their interesting fields into all book search systems they use. Our approach provides the sharing of users' profile with their interesting fields by enabling user's interesting fields to be described over each book classification ontology of various book information providers. We also provide a middleware that manages users' profiles written in RDF and analizes similarity between user's interesting field and each concept over the book classification ontology. Our approach provide better performance than traditional keyword-based search by sharing the user's profile among book recommendation systems.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.47-56
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• 2015

Automated detection of interesting web pages could be used in many different application domains. Determining a user's interesting web pages can be performed implicitly by observing the user's behavior. The task of distinguishing interesting web pages belongs to a classification problem, and we choose white box learning methods (fixed effect logit regression and support vector machine) to test empirically. The result indicated that (1) fixed effect logit regression, fixed effect SVMs with both polynomial and radial basis kernels showed higher performance than the linear kernel model, (2) a personalization is a critical issue for improving the performance of a model, (3) when asking a user explicit grading of web pages, the scale could be as simple as yes/no answer, (4) every second the duration in a web page increases, the ratio of the probability to be interesting increased 1.004 times, but the number of scrollbar clicks (p=0.56) and the number of mouse clicks (p=0.36) did not have statistically significant relations with the interest.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.569-576
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• 2008

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. Association rule is an interesting rule among purchased items in transaction, but the negative association rule is an interesting rule that includes items which are not purchased. Boolean Analyzer is the method to produce the negative association rule using PIM. But, PIM is subjective. In this paper, we present statistical objective criterion in negative association rules using Boolean Analyzer.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.145-151
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• 2006

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule support and confidence and lift. Association rule is an interesting rule among purchased items in transaction, but the negative association rule is an interesting rule that includes items which are not purchased. Boolean Analyzer is the method to produce the negative association rule using PIM. But PIM is subjective. In this paper, we present statistical objective criterion in negative association rules using Boolean Analyzer.

• Bulletin of the Korean Chemical Society
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• v.32 no.spc8
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• pp.2921-2927
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• 2011

This paper describes efficient synthetic approaches for isolating biologically interesting natural pyranochalcones and their unnatural derivatives from Mallotus Philippensis. The key strategies involve ethylenediamine diacetate-catalyzed benzopyran formation reactions and base-catalyzed aldol reactions.

• Bulletin of the Korean Chemical Society
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• v.28 no.10
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• pp.1739-1745
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• 2007

A new methodology for the preparation of pyranochromenes was developed starting from substituted trihydroxybenzenes. This methodology was applied successfully to the total synthesis of biologically interesting compounds, clusiaphenone A, octandrenolone, O-methyloctandrenolone, trans-3''',4'''-dihydro- 3''',4'''-dihydroxy-O-methyloctandrenolone, trans-3'',4''-dihydro-3'',4''-dihydroxy-O-methyloctandrenolone, flemiculosin, laxichalcone, and racemic 3-deoxy-Ms-II.

• Bulletin of the Korean Chemical Society
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• v.26 no.12
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• pp.1933-1936
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• 2005

Total synthesis of biologically interesting $({\pm})$-cannabichromene, $({\pm})$-cannabichromenic acid, and $({\pm})$-daurichromenic acid is described. The key step in the synthetic strategy involves the formation of benzopyrans by ethylenediamine diacetate-catalyzed reactions of resorcinols with $\alpha$,$\beta$-unsaturated aldehydes.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1221-1228
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• 2011

Recently, several mathematicians have studied some interesting relations between extended q-Euler number and Bernstein polynomials(see [3, 5, 7, 8, 10]). In this paper, we give some interesting identities on the Genocchi polynomials and Bernstein polynomials.