• Title/Summary/Keyword: automatic classification

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Principles of the Automatic Book-Classification (도서분류자동화 원리유도에 관한 연구)

  • 심의순;이경호
    • Journal of Korean Library and Information Science Society
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    • v.11
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    • pp.175-209
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    • 1984
  • The purpose of this study is to build a general principle for the automatic book-classification which can be put to use in library operation, and to present a methodology of the automatic classification for the library. Since the enumerative classification scheme which exist as manual systems cannot be a n.0, pplied to the automation of classification, the principles of Colon Classification by S.R. Ranganathan is brought in and studied. The result of the study can be summarized as follows: (1) Automatic book-classification can be performed by the principles of faceted classification. (2) This study presents a general and an a n.0, pplication principles for the automatic book-classification. (3) File design for the automatic book-classification of a general classification is different from that of special classification, (4) The methodology is to classify the literature by inputting the title into a terminal. In addition, the expected Value from the Automatic Book-classification is as follows: (1) The prompt and accurate process of classification is possible. (2) Though a book is classified in any library it can have the same classification number. (3) The user can retrieve the classification code of a book for which he or she wants to search through the dialogue with the computer. (4) Since the concept coordination method is employed, even the representing of a multi-subject concept is made simple. (5) By performing automatic book-classification, the automation of library operation can be completed.

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Developing an Automatic Classification System Based on Colon Classification: with Special Reference to the Books housed in Medical and Agricultural Libraries (콜론분류법에 바탕한 자동분류시스템의 개발에 관한 연구 - 농학 및 의학 전문도서관을 사레로 -)

  • Lee Kyung-Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.23
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    • pp.207-261
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    • 1992
  • The purpose of this study is (1) to design and test a database which can be automatically classified, and (2) to generate automatic classification number by processing the keywords in titles using the code combination method of Colon Classification(CC) as well as an automatic recognition of subjects in order to develop an automatic classification system (Auto BC System) based on CC which can be applied to any research library. To conduct this study, 1,510 words in the fields of agricultrue and medicine were selected, analized in terms of [P], [M], [E], [S], [T] employed in CC, and included in a database for classification. For the above-mentioned subject fields, the principle of an automatic classification was specified in order to generate automatic classification codes as well as to perform an automatic subject recognition of the titles included. Whenever necessary, editing, deleting, appending and reindexing of a database can be made in this automatic classification system. Appendix 1 shows the result of the automatic classification of books in the fields of agriculture and medicine. The results of the study are summarized below. 1. The classification number for the title of a book can be automatically generated by using the facet principles of Colon Classification. 2. The automatic subject recognition of a book is achieved by designing a database making use of a globe-principle, and by specifying the subject field for each word. 3. The automatic subject-recognition of input data is achieved by measuring the number of searched words by each subject field. 4. The combination of classification numbers is achieved by flowcharting of classification formular of each subject field. 5. The efficient control of classification numbers is achieved by designing control codes on the database for classification. 6. The automatic classification by means of Auto BC has been proved to be successful in the research library concentrating on a Single field. The general library may have some problem in employing this system. The automatic classification through Auto BC has the following advantages: 1. Speed of the classification process can be improve. 2. The revision or updating of classification schemes can be facilitated. 3. Multiple concepts can be expressed in a single classification code. 4. The consistency of classification can be achieved with the classification formular rather than the classifier's subjective judgement. 5. A user's retrieving process can be made after combining the classification numbers through keywords relating to the material to be searched. 6. The materials can be classified by a librarian without subject backgrounds. 7. The large body of materials can be quickly classified by means of a machine processing. 8. This automatic classification is expected to make a good contribution to design of the total system for library operations. 9. The information flow among libraries can be promoted owing to the use of the same program for the automatic classification.

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도서분류자동화를 위한 지식베이스의 설계에 관한 연구

  • 이경호
    • Journal of Korean Library and Information Science Society
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    • v.18
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    • pp.139-192
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    • 1991
  • Though the computer has become deeply entrenched as the major tool in information processing(library works), it may be obvious that automatic book classification techniques ate still under experimentation, and the techniques have not yet been tested against the criterion of usefulness. The purpose of this study is to design of knowledge base for automatic book classification which can be put to use in library operation, and to present a methodology of application of the automatic classification into the library. Since the enumerative classification schemes which are existing are manual systems, it cannot be applied to the automatic classification, the principle of faceted classification based on concept analysis is brought in and studied. The result of this study are summarized as follows : 1. The design of knowledge base confined the field of agriculture and medicine. 2. If title is entered by the computer keyboard it will be searched in knowledge base, and then be classified by the principle of automatic classification. 3. Program flowcharts are designed as a bases of classification procedures for automatic subject recognition and classification. 4. 283 books in agriculture, 196 books in medicine were drawn at random from Taegu University Library and Young-Nal Medical Center Library respectively. 5. The experiment of automatic classification is performed 143 books in agriculture 166 books in medicine except for other subject books. 6. It was proved that automatic book classification is possible by design of knowledge base. In addition the expected values from design of knowledge base for automatic book classification are as follows : 1. The prompt and accurate process of classification is possible. 2. Though some title is classified in any library, it can be classified the some classification number by a program. 3. The user can retrieve the classification codes of books for which he or she wants to search through the computer. 4. Since the concept coordination method is employed the representing of a multisubject concept is make simple. 5. By performing automatic book classification the automation of total system can be achieved. 6. The efficient international information transfer will be advanced since all the institution maintain unified classification number.

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Developing an Automatic Classification System for Botanical Literatures (식물학문헌을 위한 자동분류시스템의 개발)

  • 김정현;이경호
    • Journal of Korean Library and Information Science Society
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    • v.32 no.4
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    • pp.99-117
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    • 2001
  • This paper reports on the development of an automatic book classification system using the faced classification principles of CC(Colon Classification). To conduct this study, some 670 words in the botanical field were selected, analyzed in terms [P], [M], [E], [S], [T] employed in CC 7, and included in a database for classification. The principle of an automatic classification system is to create classification numbers automatically through automatic subject recognition and processing of key words in titles through the facet combination method of CC. Particularly, a classification database was designed along with a matrix-principle specifying the subject field for each word, which can allow automatic subject recognition possible.

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CC의 구조적 분석을 통한 분류자동화 원리유도

  • 이경호
    • Journal of Korean Library and Information Science Society
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    • v.15
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    • pp.113-151
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    • 1988
  • The enumerative classification schemes do not represent the tiny mass of knowledge embodied in a article in a periodical or in a chapter or a paragraph of a book. But today's information centers regard a tiny spot of knowledge embodied in a article as a class. we call this micro-thought. But the enumerative classification are manual systems, it cannot be a n.0, pplied to the automation of classification. The purpose of this study is to build a general principle for the automatic book-classification which can be put to use in library operation, and to present a methodology of the automatic classification for the library. The methodology used is essentially theoretical, Published works by and about Ranganathan, especially 6th edition of the CC were studied, analyzed. The principle of automatic book classification derived from the analysis of colon classification and facet combinations. The results of this study can be summarized as follows ; (1) This study confined the fields of library science and agriculture. (2) This study represent a general principles for the automatic book classification of library science and agriculture. (3) Program flowcharts are designed as a basis of system analysis and program procedure in library science and agriculture. (4) The principles of the automatic classification in library, science is different from that of agriculture. (5) Automatic book classification can be performed by the principle of faceted classification, by inputting the title and subject code into a computer. In addition, the expected value from the automatic book-classification is as follows (1) The prompt and accurate of classification is possible. (2) Though a book is classified in any library, it can have same classification number. (3) The user can retrieve the classification code of a book for which he or she wants to search through dialogue with the computer. (4) Since the concept coordination method is employed, a tiny mass of knowledge embodied in a article in a periodical or in a chapter or a paragraph of a book can be represented as a class. (5) By performing automatic book-classification, the automation of library operation can be completed.

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Feature Extraction of Non-proliferative Diabetic Retinopathy Using Faster R-CNN and Automatic Severity Classification System Using Random Forest Method

  • Jung, Younghoon;Kim, Daewon
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.599-613
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    • 2022
  • Non-proliferative diabetic retinopathy is a representative complication of diabetic patients and is known to be a major cause of impaired vision and blindness. There has been ongoing research on automatic detection of diabetic retinopathy, however, there is also a growing need for research on an automatic severity classification system. This study proposes an automatic detection system for pathological symptoms of diabetic retinopathy such as microaneurysms, retinal hemorrhage, and hard exudate by applying the Faster R-CNN technique. An automatic severity classification system was devised by training and testing a Random Forest classifier based on the data obtained through preprocessing of detected features. An experiment of classifying 228 test fundus images with the proposed classification system showed 97.8% accuracy.

A Study on the Algorithm for Underwater Target Automatic Classification using the Passive Sonar (수동소나를 이용한 수중물체 자동판별기법 연구)

  • 이성은;최수복;노도영
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.1
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    • pp.76-84
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    • 2000
  • As first step of any acoustic defence system, a attacking target warning system needs to be extremely reliable. This means the system must ensure a high probability of target classification together with a very low false alarm rate. In this paper, a algorithms for underwater target automatic classification is available for use in the passive sonar will be presented. In first, we will describe the precise automatic extraction of frequency lines for the detection of acoustic signatures. Also, a neural network and fuzzy based algorithms for target classification will be described. Thus the performances of these algorithms are very good with a high probability of classification.

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Study on Automated Land Cover Update Using Hyperspectral Satellite Image(EO-1 Hyperion) (초분광 위성영상 Hyperion을 활용한 토지피복지도 자동갱신 연구)

  • Jang, Se-Jin;Chae, Ok-Sam;Lee, Ho-Nam
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.383-387
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    • 2007
  • The improved accuracy of the Land Cover/Land Use Map constructed using Hyperspectal Satellite Image and the possibility of real time classification of Land Use using optimal Band Selective Factor enable the change detection from automatic classification using the existed Land Cover/Land Use Map and the newly acquired Hyperspectral Satellite Image. In this study, the effective analysis techniques for automatic generation of training regions, automatic classification and automatic change detection are proposed to minimize the expert's interpretation for automatic update of the Land Cover/Land Use Map. The proposed algorithms performed successfully the automatic Land Cover/Land Use Map construction, automatic change detection and automatic update on the image which contained the changed region. It would increase applicability in actual services. Also, it would be expected to present the effective methods of constructing national land monitoring system.

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Design of Automatic Records Classification System Using Contextual Information (맥락정보를 이용한 기록 자동분류시스템 설계)

  • Jang, Ji-Sook;Rieh, Hae-Young
    • Journal of Korean Society of Archives and Records Management
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    • v.9 no.1
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    • pp.151-173
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    • 2009
  • The classification in the Records and Archives Sciences focuses on the contextual information in producing and utilizing records rather than their contents. This study aimed at designing an automatic records classification system to enable an automatic classification focusing on the aggregation of the context of records rather than the contents of individual record in the classification scheme, structured on the basis of business activities analyses for records reflecting the business activities. The automatic records classification system was designed to have mutual supplements by constructing the classification scheme and thesaurus together as the classification reference, as well as the aggregation of records that have been already classified. Additionally included are plans to apply the classified contextual information of records to the classification reference on the real-time base right after the category assignment of records to be classified. Although there are limitations as the designed system depends on the quality of the contextual information, it is considered that the system could lead to ensure that the contextual information of records should be more substantial.

Comparison of Performance Factors for Automatic Classification of Records Utilizing Metadata (메타데이터를 활용한 기록물 자동분류 성능 요소 비교)

  • Young Bum Gim;Woo Kwon Chang
    • Journal of the Korean Society for information Management
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    • v.40 no.3
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    • pp.99-118
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    • 2023
  • The objective of this study is to identify performance factors in the automatic classification of records by utilizing metadata that contains the contextual information of records. For this study, we collected 97,064 records of original textual information from Korean central administrative agencies in 2022. Various classification algorithms, data selection methods, and feature extraction techniques are applied and compared with the intent to discern the optimal performance-inducing technique. The study results demonstrated that among classification algorithms, Random Forest displayed higher performance, and among feature extraction techniques, the TF method proved to be the most effective. The minimum data quantity of unit tasks had a minimal influence on performance, and the addition of features positively affected performance, while their removal had a discernible negative impact.