• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.219-228
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• 2018

This study conducted to identify the impact of organizational factors on the characteristics of category management system, market orientation and collaboration orientation, in domestic retail industry, and also to identify the relationship between organizational factors and category management system's characteristics varies depending on the business type, retailer and supplier. To accomplish these research purposes, the study performed statistical analyses using a total of 94 samples. The results of the study can be summarized as follows. First, the organizational factors that affect market orientation of the category management system were found to be information technology infrastructure and organizational management system, and the organizational factors that affect collaborative orientation of the category management system were found to be partnerships and organizational management systems. Second, the relationship between market orientation and collaborative orientation of the category management system does not differ by the business type.

• Korean Journal of Mathematics
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• v.21 no.2
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• pp.189-195
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• 2013

PosM is a category whose objects are ample spaces and morphisms are possibility mappings. We study some properties of the Category PosM. So we show that Category PosM is a cartesian closed category, and it forms a topos with some condition.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.351-355
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• 2009

The amount of incoming e-mails is increasing rapidly due to the wide usage of Internet. We often group e-mails into categories for maintaining e-mail efficiently. However reading the email messages and classifying them is still tedious task. Moreover, the number of e-mails and manual classifying is increasing everyday. So, automatic e-mail classification is important techniques. In this paper, we propose a multi-way e-mail classification method that uses PCA for automatic category generation and dynamic category hierarchy for re-organizing e-mail categories. It classifies a huge amount of receiving e-mail messages automatically, efficiently, and accurately.

• Asia pacific journal of information systems
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• v.16 no.3
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• pp.159-176
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• 2006

Collaborative filtering is one of the popular techniques for personalized recommendation in e-commerce. In collaborative filtering, user profiles are usually managed per product category in order to reduce data sparsity. Product diversification of Internet storefronts and multiple product category sales of e-commerce portals require cross-product category usage of user profiles in order to overcome the cold start problem of collaborative filtering. In this paper, we study the feasibility of cross-product category usage of user profiles, and suggest a method to improve recommendation performance of cross-product category user profiling. First, we investigate whether user profiles on a product category can be used to recommend products in other product categories. Furthermore, a way of utilizing user profiles selectively is suggested to increase recommendation performance of cross-product category user profiling. The feasibility of cross-product category user profiling and the usefulness of the proposed method are tested with real click stream data of an Internet storefront which sells multiple product categories including books, music CDs, and DVDs. The experiment results show that user profiles on a product category can be used to recommend products in other product categories. Also, the selective usage of user profiles based on correlations between subcategories of two product categories provides better performance than the whole usage of user profiles.

• International Journal of Contents
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• v.1 no.2
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• pp.26-30
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• 2005

According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

• Korean Journal of Culture and Social Issue
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• v.12 no.4
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• pp.55-75
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• 2006

Most previous research on impression formation has been examined the effects of various informations exclusively within a category, either social category or individual characteristic. The present research examined and compared the priming effects of social category information (we and other) versus personality information (warm and cold) on impression formation. In Study 1, participants primed subliminally with combinations of social category and personality information (we/warm, we/cold, other/warm, and other/cold) were asked to rate faceial pictures on the good-bad and likable-dislikable dimensions. The analysis revealed only the significant main effects of social category information but not any effects of personality information on both the impression dimensions. In Study 2 in which participants were primed with either social category or personality information exclusively, priming of social category information influenced the judgments of likable-dislikable dimension and that of personality information influenced the judgments of good-bad dimension. These results suggest that personality information influences impression in general even though its impacts may be overwritten by social categorical information. The findings were discussed with its implication of everyday's impression formation and the cultural psychological perspectives.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.268-273
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• 2013

In this paper, we propose a document classification model using Web documents as a part of the training corpus in order to resolve the imbalance of the training corpus size per category. For the purpose of retrieving the Web documents closely related to each category, the proposed document classification model calculates the matching score between word features and each category, and generates a Web search query by combining the higher-ranked word features and the category title. Then, the proposed document classification model sends each combined query to the open application programming interface of the Web search engine, and receives the snippet results retrieved from the Web search engine. Finally, the proposed document classification model adds these snippet results as Web documents to the training corpus. Experimental results show that the method that considers the balance of the training corpus size per category exhibits better performance in some categories with small training sets.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05b
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• pp.253-257
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• 2009

General technique and management technology of agriculture have development in every year to ensure the competitiveness of agriculture. Accordingly, Interested in using information systems management technology is improving. For information system, the first system of rural buildings category should be established. Classification system is set up through each specific code. and it takes advantage of the information system is to achieve the computerization of agricultural society. Therefore, in this study construction information classification system, quantity of output category, got to the standard classification system architecture, apply to agricultural buildings to review the situation and saw a problem. The result, it is the complexity and broad scope, and it is set to inappropriate setting of the Category item.

• Journal of KIISE
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• v.44 no.9
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• pp.946-953
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• 2017

Semantic Role Decision defines the semantic relationship between the predicate and the arguments in natural language processing (NLP) tasks. The semantic role information and semantic category information should be used to make Semantic Role Decisions. The Sejong Electronic Dictionary contains frame information that is used to determine the semantic roles. In this paper, we propose a method to extend the Sejong electronic dictionary using word embedding and synonyms. The same experiment is performed using existing word-embedding and retrofitting vectors. The system performance of the semantic category assignment is 32.19%, and the system performance of the extended semantic category assignment is 51.14% for words that do not appear in the Sejong electronic dictionary of the word using the word embedding. The system performance of the semantic category assignment is 33.33%, and the system performance of the extended semantic category assignment is 53.88% for words that do not appear in the Sejong electronic dictionary of the vector using retrofitting. We also prove it is helpful to extend the semantic category word of the Sejong electronic dictionary by assigning the semantic categories to new words that do not have assigned semantic categories.

• Spatial Information Research
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• v.23 no.1
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• pp.33-40
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• 2015

Recently, land pollution makes various environment problems according to existing land use. So, there is an urgent need for management about these problems. This study categorize land pollution area using the land category information according to main land usage for reasonable analysis of land pollution area by point and non-point pollution sources. And also there was able to collect land pollution sources information efficiently by analysing the land category information. The land use information that categorized important factor for management and land pollution survey will be utilized Soil environment management and preservation. And land use information will be used land use regulation, resonable preservation and management.