• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.501-506
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• 2002

사람은 누구나 잭이나 문서를 읽을 때 중요한 부분에 강조, 해설, 설명을 하기 위해서 표시를 하거나 글을 입력한다. 이와 같이 원본문서에 추가되는 부가 정보를 Annotation이라고 한다[6][7]. Annotation을 이용하면 차후에 원본문서를 재창조하거나 다른 사람이 원본문서를 참조할 경우 과중한 정보의 양을 극복할 수 있으므로[4], 원본문서의 이해도를 향상시킬 수 있다. 따라서, Annotation은 한번 사용하고 그치는 정보가 아닌 재사용할 수 있는 점보임을 의미한다[1,2,3]. 이러한 Annotation 기능을 웹 문서에 적용하게 되면 종이문서에서 얻을 수 있는 장점뿐만 아니라 웹 환경의 특징인 공유[5], 검색[4], 재편집 등의 기능이 가능하다. 이와 관련한 많은 연구가 진행중에 있다. 그러나, 기존의 Annotation 연구는 Anchor 입력된 다수의 Annotation이 무의미한 출력 순서로 제공되고 있으며, 또한 Anchor에 입력된 Annotation의 출력으로 인해 문서 구조가 변경되거나, 가려지는 등의 문제점으로 사용자들이 쉽게 사용 및 이해할 수 있는 Annotation 출력 인터페이스에 대한 연구가 부족한 실정이다. 따라서, 본 논문에서는 Anchor에 입력된 다수의 Annotation들 간의 의미적 순서를 부여하여 보다 적절한 Annotation에 대한 우선 접근이 가능하도록 계층적인 Annotation 우선처리 기법을 제안하고, Annotation 출력으로 인한 문서 변경 문제를 해결하기 위한 유동적인 Annotation 표현 기법을 제안한다. 또한 Annotation이 문서에 부가된 부가정보의 역할을 뿐만 아니라, 다양한 활용이 가능하도록 XML 표준에 기반한 저장 구조를 지원하며, 원본문서와 분리하여 저장한다.속도를 개선시켰고, 국소적인 변형이 있는 패턴과 특징의 수가 다른 패턴의 경우에도 좋은 인식률을 얻었다.r interferon alfa concentrated solution can be established according to the monograph of EP suggesting the revision of Minimum requirements for biological productss of e-procurement, e-placement, e-payment are also investigated.. monocytogenes, E. coli 및 S. enteritidis에 대한 키토산의 최소저해농도는 각각 0.1461 mg/mL, 0.2419 mg/mL, 0.0980 mg/mL 및 0.0490 mg/mL로 측정되었다. 또한 2%(v/v) 초산 자체의 최소저해농도를 측정한 결과, B. cereus, L. mosocytogenes, E. eoli에 대해서는 control과 비교시 유의적인 항균효과는 나타나지 않았다. 반면에 S. enteritidis의 경우는 배양시간 4시간까지는 항균활성을 나타내었지만, 8시간 이후부터는 S. enteritidis의 성장이 control 보다 높아져 배양시간 20시간에서는 control 보다 약 2배 이상 균주의 성장을 촉진시켰다.차에 따른 개별화 학습을 가능하게 할 뿐만 아니라 능동적인 참여를 유도하여 학습효율을 높일 수 있을 것으로 기대된다.향은 패션마케팅의 정의와 적용범위를 축소시킬 수 있는 위험을 내재한 것으로 보여진다. 그런가 하면, 많이 다루어진 주제라 할지라도 개념이나 용어가 통일되지 않고 사용되며 검증되어 통용되는 측정도구의 부재로 인하여 연구결과의 축적이 미비한 상태이다. 따라서, 이에 대한 재고와 새로운 방향

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.194-207
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• 2003

This paper presents an optimal design methodology for the multidimensional nested attribute index (MD-NAI) that uses a multidimensional index structure for indexing the nested attributes in object databases. The MD-NAI efficiently supports complex queries involving both nested attributes and class hierarchies, which are not supported by the nested attribute index using one-dimensional index structure such as $B^+$-tree. However, the performance of the MD-NAI is very degraded in some cases of user's query types. In this paper, for the performance enhancement of the MD-NAI, we first determine the optimal shape of index page region by using the query information about the nested predicates, and then construct an optimal MD NAI by applying a region splitting strategy that makes the shape of the page regions of the MD-NAI as close as possible to the predetermined optimal one. For performance evaluation, we perform extensive experiments with the MD-NAI using various types of nested predicates and object distribution. The results indicate that our proposed method builds optimal MD-NAI regardless of the query types and object distributions. When the interval ratio of a three-dimensional query region is 1:16:236, the performance of the proposed method is enhanced by as much as 5.5 times over that of the conventional method employing the cyclic splitting strategy.

• Information Systems Review
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• v.22 no.4
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• pp.75-92
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• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.