• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.9-23
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• 2019

In this paper, we propose a layer structure of a pest image classifier model using CNN (Convolutional Neural Network) and background removal image processing algorithm for improving classification accuracy in order to build a smart monitoring system for pine wilt pest control. In this study, we have constructed and trained a CNN classifier model by collecting image data of pine wilt pest mediators, and experimented to verify the classification accuracy of the model and the effect of the proposed classification algorithm. Experimental results showed that the proposed method successfully detected and preprocessed the region of the object accurately for all the test images, resulting in showing classification accuracy of about 98.91%. This study shows that the layer structure of the proposed CNN classifier model classified the targeted pest image effectively in various environments. In the field test using the Smart Trap for capturing the pine wilt pest mediators, the proposed classification algorithm is effective in the real environment, showing a classification accuracy of 88.25%, which is improved by about 8.12% according to whether the image cropping preprocessing is performed. Ultimately, we will proceed with procedures to apply the techniques and verify the functionality to field tests on various sites.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.258-266
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• 2023

Aiming at the problems of poor customer satisfaction and poor accuracy of customer classification, this paper proposes a customer classification model based on speech recognition. First, this paper analyzes the temporal data characteristics of customer demand data, identifies the influencing factors of customer demand behavior, and determines the process of feature extraction of customer voice signals. Then, the emotional association rules of customer demands are designed, and the classification model of customer demands is constructed through cluster analysis. Next, the Euclidean distance method is used to preprocess customer behavior data. The fuzzy clustering characteristics of customer demands are obtained by the fuzzy clustering method. Finally, on the basis of naive Bayesian algorithm, a customer demand classification model based on speech recognition is completed. Experimental results show that the proposed method improves the accuracy of the customer demand classification to more than 80%, and improves customer satisfaction to more than 90%. It solves the problems of poor customer satisfaction and low customer classification accuracy of the existing classification methods, which have practical application value.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.419-448
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• 2013

This study is to describe the principles and outcome of the development for a classification scheme of presidential records to manage efficiently and provide them as archival information service productively. First, this scheme accommodates a management aspect, taking consideration into the aspect of archival records as the results of government administrative duties. Additionally, governance aspects are embraced into this scheme since presidential records can be seen as the results of governing purpose. We are considering the functional aspects of the public records too. As a result, this scheme adopts both management and governance aspect. Focusing on reflecting both functional and governance aspects, first analyzes existing classification systems in domestic and abroad. Finally, this study proposes 24 first-level, 114 second-level, and 179 third-level classification categories. Archivists and classification experts examined the classification scheme for verification by advisory meetings.

• Journal of the Korean Society for information Management
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• v.22 no.4 s.58
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• pp.5-22
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• 2005

As the development of advertising industry and media the research about an advertisement get accomplished. As the result information resources called on the advertising materials are on an Increasing trend. However, it looks into the classification system In advertising field of KDC, the problems are as the follows : (1) the classification items are too incomplete, (2) the main class is badly arranged. The reason have no regard for the correlation with a science. So, it gives rise to confusion to the librarian and user. The purpose of the study is to present the improvement plan on the classification system in advertising field of KDC. In order to build the improvement plan, the four steps are utilized. The first step Is to investigate the characteristic of sciences on advertising and a type. The second one is to survey the current status of the library classification as KDC, NDC, DDC, and LCC. The third one is to analyse the classification system of library and web site on the advertising. The forth one is to grasp the problems on the classification system In advertising field of KDC.

• Journal of the Korean Society for Library and Information Science
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• v.26
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• pp.187-212
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• 1994

The present study examines the characteristics of the international literature of classification systems published in the period 1981-1990. The references in the 'Classification Literature' sections of International Classification and the references in these source items were examined. The present study focused on analyzing each of the following characteristics: format, subject, language, geographical origin, age, authorship and number of references. The findings from the data analyses show clearly that in the literature of classification systems, I) books were the most frequently cited format; 2) library and information science was the most frequently cited subject; 3) English was the major language; 4) the literature of each classification system was written predominently in English except for Library Bibliographic Classification; 5) the language of each source item was the same as that of the greatest number of references of that source item: 6) the U.S., Germany, India, Russia, and the U.K. were the major geographic origin of publication; 7) there was a very close relationship between country of publication and language: 8) the country of origin of the documents was cited more than any other country except for the U.S.: 9) Price's Index of the literature revealed that the literature was a soft science and the half-life of the literature was about 7.5 years; 10) there was a preponderance of single authorships; 11) the literature was not a scholarly or scientific literature, according to the average number of references in source items and the percentage of unreferenced items. The findings of this reference study provide a better understanding of the characteristics of the classification systems literature. They prove useful for the collection development and assist classification systems researchers to prepare linguistically for their careers and encourage international communication efforts.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.1
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• pp.25-44
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• 2013

The purpose of this study was to analyze the trends of Classification Studies in Korea from 205 research articles in five scholarly journals in Library and Information Science during the period 1986-2011. Individual article was analyzed in the aspects of specific research topics, research methodologies, data collection & analysis, and the characteristics of classification research was suggested. The amount of research paper has increased during the period and the focus of the study was on practical use and most of the papers were about new classification schedules or modification of current classification systems. Most of the papers were literature research and comparative research on classification systems by professors or graduate students. Top 9 authors in classification research were professors or lecturers and a few authors were computer science major. Therefore, various research topics, research methodologies and collaborations with other disciplines are necessary for future classification research.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.477-497
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• 2008

Mood classification of blog text is an interesting problem, with a potential for a variety of services involving the Web. This paper introduces an approach to mood classification enhancements through the normalized negation n-grams which contain mood clues and corpus-specific term weighting(CSTW). We've done experiments on blog texts with two different classification methods: Enhanced Mood Flow Analysis(EMFA) and Support Vector Machine based Mood Classification(SVMMC). It proves that the normalized negation n-gram method is quite effective in dealing with negations and gave gradual improvements in mood classification with EMF A. From the selection of CSTW, we noticed that the appropriate weighting scheme is important for supporting adequate levels of mood classification performance because it outperforms the result of TF*IDF and TF.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.3
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• pp.29-51
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• 2013

The purpose of this study is to develop internal tables in Christian religion in the 5th edition of Korean Decimal Classification. The scope of the Christianity, its structure of various classification schemes, and the concepts of internal tables were analyzed. The contents of several textbooks were analyzed for the scope of the discipline and the classification schemes and internal tables of DDC, UDC, NDC, LCC, Classification of the Library of Union Theological Seminary and the Classification of the Korea Theological Library were compared. And then, internal tables in Bible, sermon, worship, church history were built and those tables were evaluated by librarians and experts in the fields. And finally, internal tables of the Christiainity and new headings were suggested. New internal tables in Christianity will increase the effectiveness of information retrieval and it will provide a foundation for developing internal tables in other disciplines.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.15-37
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• 2013

The purpose of this study is to develop a faceted classification that enables the conceptualization and the organization of Korean food information. 23,470 terms were collected, categorized, and analyzed from the table of contents in 776 monographs and directory headings in portal sites related to Korean food. In order to develop the Korean food classification, common properties were analyzed in the process of categorizing terms. Then basic facets and subfacets were defined and assigned, and hierarchies among facets and concepts, citation orders, and notations were decided. As a result, the classification scheme consisted of 16 basic facets and 85 subfacets. The citation order of facets was proposed in order of Personality facet (kinds of dishes), Matter facet (materials, cooking utensils/equipment/containers, and nutrients), Energy facet (cooking processes and techniques, eating sense, type of cooking, table services, and agents of cooking), Space facet (countries/ethnic groups/geography, and eating places), Time facet (situation/purposes, season, time of meals, periods, and ages). The result of this study will be used for organizing, searching, retrieving, and providing Korean food information effectively around the world. Also, it will provide a foundation for developing subject-oriented classification using facet analysis in other disciplines.