• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.856-868
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• 2007

We propose an effective method for block classification in a document image. The gray level document image is converted to the binary image for a block segmentation. This binary image would be smoothed to find the locations and sizes of each block. And especially during this smoothing, the inner block heights of each block are obtained. The gray level image is divided to several blocks by these location informations. The SGLDM(spatial gray level dependence matrices) are made using the each gray-level document block and the seven second-order statistical texture features are extracted from the (0,1) direction's SGLDM which include the document attributes. Document image blocks are classified to two groups, text and non-text group, by the inner block height of the block at the nearest neighbor rule. The seven texture features(that were extracted from the SGLDM) are used for the five detail categories of small font, large font, table, graphic and photo blocks. These document blocks are available not only for structure analysis of document recognition but also the various applied area.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.30-38
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• 2011

This paper proposes a new enhancing document clustering method using a synonym of cluster topic and the similarity. The proposed method can well represent the inherent structure of document cluster set by means of selecting terms of cluster topic based on the semantic features by NMF. It can solve the problem of "bags of words" by using of expanding the terms of cluster topics which uses the synonyms of WordNet. Also, it can improve the quality of document clustering which uses the cosine similarity between the expanded cluster topic terms and document set to well cluster document with respect to the appropriation cluster. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.763-782
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• 2019

This paper proposes a probabilistic document ranking model incorporating term dependencies. Document ranking is a fundamental information retrieval task. The task is to sort documents in a collection according to the relevance to the user query (Qin et al., Information Retrieval Journal, 13, 346-374, 2010). A probabilistic model is a model for computing the conditional probability of the relevance of each document given query. Most of the widely used models assume the term independence because it is challenging to compute the joint probabilities of multiple terms. Words in natural language texts are obviously highly correlated. In this paper, we assume a multinomial distribution model to calculate the relevance probability of a document by considering the dependency structure of words, and propose an information retrieval model to rank a document by estimating the probability with the maximum entropy method. The results of the ranking simulation experiment in various multinomial situations show better retrieval results than a model that assumes the independence of words. The results of document ranking experiments using real-world datasets LETOR OHSUMED also show better retrieval results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2607-2613
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• 2012

The results of inherent knowledge based generic summarization are influenced by the composition of sentence in document set. In order to resolve the problem, this papser propses a new generic document summarization which uses clustering of semantic feature of document and coherence of document cluster. The proposed method clusters sentences using semantic feature deriving from NMF(non-negative matrix factorization), which it can classify document topic group because inherent structure of document are well represented by the sentence cluster. In addition, the method can improve the quality of summarization because the importance sentences are extracted by using coherence of sentence cluster and the cluster refinement by re-cluster. The experimental results demonstrate appling the proposed method to generic summarization achieves better performance than generic document summarization methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1402-1408
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• 2013

Document managements are very important in internal communication for good performance on projects. In case of small scale projects, the document management criteria often have very different from each of the cooperation departments and changes of document structure of work process are frequent over a project period. In this thesis, we propose a monitoring system of document management which is based on P2P(Peer-to-Peer). The proposed monitoring system of document management, which is based on P2P, makes up for time limits and a specific work process in small scale project groups. It can be managed focusing on work process and can monitor effectively the status of creations, sharing and distributions of documents. We can be installed at a low cost by using P2P in a small scale project.

• Journal of the Korean Society for information Management
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• v.21 no.1
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• pp.93-117
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• 2004

This study is to develop a hierarchic clustering model fur document classification and browsing in OPAC systems. Two automatic indexing techniques (with and without controlled terms), two term weighting methods (based on term frequency and binary weight), five similarity coefficients (Dice, Jaccard, Pearson, Cosine, and Squared Euclidean). and three hierarchic clustering algorithms (Between Average Linkage, Within Average Linkage, and Complete Linkage method) were tested on the document collection of 175 books and theses on library and information science. The best document clusters resulted from the Between Average Linkage or Complete Linkage method with Jaccard or Dice coefficient on the automatic indexing with controlled terms in binary vector. The clusters from Between Average Linkage with Jaccard has more likely decimal classification structure.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.455-462
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• 1997

SGML(Standard Generalized Markup Language) is the ISO standard fer describing the logical structure of documents and is also adopted as the CALS standard for document description. Since then, there have been growing interests in SGML application in a variety of fields. However because SGML doesn't provide a standard method for describing various processing informations, ie, formatting and transformation, most applications have applied methods that are system dependent. Recently, ISO defined DSSSL(Document Style Semantics and Specification Language) as a standard mechanism to specify the formatting, transformation and retrieval of structured documents. Therefore, in this paper, we present a DSSSL processing system far style control of structured documents such as SGML documents. The system processes DSSSL style sheet that describes layout of documents and browses the result of its application to a SGML document. We have conducted tests on a lot of SGML documents and DSSSL style sheets successfully. Now, we are developing the SGML document management system that supports creation, editing, storage and retrieval of SGML document based upon the DSSSL processor and the SGML parser which we have developed.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.132-140
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• 2007

The quality of the camera image is worse than that of the scanner image because of lighting variation and inaccurate focus. This paper proposes a binarization method for camera-based document recognition, which is tolerant to low-quality camera images. Based on an existing method reported to be effective in previous evaluations, we enhanced the adaptability to the image with a low contrast due to low intensity and inaccurate focus. Furthermore, applying an additional small-size window in the binarization process, it is effective to extract the fine detail of character structure, which is often degraded by conventional methods. In experiments, we applied the proposed method as well as other methods to a document recognizer and compared the performance for many cm images. The result showed the proposed method is effective for recognition of document images captured by the camera.

• Journal of the Korean Society for information Management
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• v.21 no.1
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• pp.231-251
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• 2004

This study aims to collect and manage in the step of creation metadata information to effectively manage and use official document which is a typical and normal records. To do it. data elements are extracted through analyzing structure of official document format. And we also select metadata elements reflecting creation background, publisher's intention, characteristic of official documents through evaluating and comparing extracted elements with data elements defined in ISAD rules. It would be draft data in constructing standardized metadata structure for records in Korea.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3829-3839
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• 2000

The UML(Unified Modeling Language) Class Diagram which is a part of structure of UML is fit for Object Modeling, and more recently, as the appearance of UXF(UML eXchange Format) UML Class Diagram by itself, can be exchanged in many other different system document. So this paper suggest the conversion system from UML Class Diagram to XML DTD. As this we can easily transformation and saving the UML Class Diagram that is the standard of Modeling Language to XML document which is so reusable. Also it can give a flexible method for the representation to the logical structure of document in various way because of converting XML DTD.