• Journal of the Korean Society for information Management
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• v.23 no.3 s.61
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• pp.69-89
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• 2006

Several performance factors which have applied to the automatic indexing with controlled vocabulary and text categorization based on Rocchio algorithm were examined, and the simple method for performance improvement of them were tried. Also, results of the methods using Rocchio algorithm were compared with those of other learning based methods on the same conditions. As a result, keeping with the strong points which are implementational easiness and computational efficiency, the methods based Rocchio algorithms showed equivalent or better results than other learning based methods(SVM, VPT, NB). Especially, for the semi-automatic indexing(computer-aided indexing), the methods using Rocchio algorithm with a high recall level could be used preferentially.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.120-125
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• 2000

We propose a semi-automatic and dynamic indexing algorithm for multi-media database(e.g. movie files, audio files), which are difficult to create indexes expressing their emotional or abstract contents, according to user's sensitivity by using user's histories of access to database. In this algorithm, we simply categorize data at first, create a vector space of each user's interest(user model) from the history of which categories the data belong to, and create vector space of each data(title model) from the history of which users the data had been accessed from. By continuing the above method, we could create suitable indexes, which show emotional content of each data. In this paper, we define the recurrence formulas based on the proposed algorithm. We also show the effectiveness of the algorithm by simulation result.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.283-304
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• 2008

This is to develop Intelligent Retrieval System which can automatically present early query's category terms(association terms connected with knowledge structure of relevant terminology) through learning function and it changes searching form automatically and runs it with association terms. For the reason, this theoretical study of Intelligent Automatic Indexing System abstracts expert's index term through learning and clustering algorism about automatic classification, text mining(categorization), and document category representation. It also demonstrates a good capacity in the aspects of expense, time, recall ratio, and precision ratio.

• International Journal of Contents
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• v.5 no.4
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• pp.51-54
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• 2009

In huge video databases, the effective video content indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable and recently various indexing tools for video databases have been developed. For efficient video content indexing, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to index video content using Kullback-Leibler distance defined between two histograms. Experimental results show that the proposed algorithm using Kullback-Leibler distance gives remarkable high accuracy ratios compared with several conventional algorithms to index video content.

• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.451-467
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• 2004

This paper is intended to present the theoretical analyses on automatic indexing, which is vital in the process of constructing a thesaurus browser, and clustering algorithms to construct hierarchical relations among terms as well as the methods for the automatic construction of a thesaurus browser. The methods to select the index term automatically in the web documents are studied by surveying the methods for analyzing and processing metadata which conforms to bibliographical roles of traditional paper documents in web documents. Also, the result of the study suggests to adding or involving the metadata in web documents, using the metadata automatic editor because metadata is not listed in most of the web documents.

• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.21-27
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• 1999

In this paper. we propose a new method for automatic classification of documents using the degree of similarity between words. First, we seek relevance terms using automatic indexing. Second, we found frequency in use words in documents and the degree of relevance between the words using probability model. Continuously, we extracted the set of words which is connected the relevance closely and created the profiles characterizing each classification And, with the profile we finally classified them. We experimented on classifying two groups of documents. Some documents were about Genetic Algorithm. The others were about Neural Network. The results of the experiments indicated that automatic classification with word accordance of degree enable us to manage the retrieved documents structurally.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.211-214
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• 2002

Automatic video partitioning is the first step for content-based indexing and retrieval of video data. In this paper, an efficient algorithm for scene change detection is proposed, where cumulative histogram and edge information are utilized. Experimental results have shown the effectiveness of the proposed algorithm.

• Journal of Korean Library and Information Science Society
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• v.31 no.2
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• pp.279-302
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• 2000

This study is to develop a new automatic system for the Korean thesaurus browser by which we can automatically control all the processes of searching queries such as, representation, generation, extension and construction of searching strategy and feedback searching. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of database system, automatic indexing, clustering technique, establishing and expressing thesaurus, and automatic information retrieval technique. The results proved by this system are as follows: 1)By using the new automatic thesaurus browser developed by the new algorithm, we can perform information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, information retrieval technique, and retrieval feedback. Thus it turns out that even the beginner user can easily access special terms about the field of a specific subject. 2) The thesaurus browser in this paper has such merits as the easiness of establishing, the convenience of using, and the good results of information retrieval in terms of the rate of speed, degree, and regeneration. Thus, it t m out very pragmatic.

• Journal of the Korean Society for Library and Information Science
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• v.35 no.4
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• pp.141-160
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• 2001

This study is to develop a new system for conducting the information retrieval automatically. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of automatic indexing, clustering technique, establishing and expressing term hierarchic relation, and automatic information retrieval technique. Thus this browser system can automatically control all the processes of information searching such as representation, generation and extension of queries and construction of searching strategy and feedback searching.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1527-1530
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• 2003

Video is an important and challenge media and requires sophisticated indexing schemes for efficient retrieval from visual databases. Scene change detection is the first step for automatic indexing of video data. Recently, several scene change detection algorithms in the pixel and compressed domains have been reported in the literature. However, using pixel methods are computationally complex and are not very robust in detecting scene change detection. In this paper, we propose robust abrupt scene change detection using macroblock type and DC coefficient. Experimental results show that the proposed algorithm is robust for detection of most abrupt scene changes in the compressed domain.