• The KIPS Transactions:PartB
• /
• v.11B no.4
• /
• pp.403-410
• /
• 2004

Recently, studies of image analysis, as the preprocessing stage for medical image analysis or image retrieval, are actively carried out. This paper intends to propose a way of utilizing color components for image retrieval. For image retrieval, it is based on color components, and for analysis of color, CLCM (Color Level Co-occurrence Matrix) and statistical techniques are used. CLCM proposed in this paper is to project color components on 3D space through geometric rotate transform and then, to interpret distribution that is made from the spatial relationship. CLCM is 2D histogram that is made in color model, which is created through geometric rotate transform of a color model. In order to analyze it, a statistical technique is used. Like CLCM, GLCM (Gray Level Co-occurrence Matrix)[1] and Invariant Moment [2,3] use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. However, even though GLCM and Invariant Moment are optimized in each domain, it is impossible to perfectly interpret irregular data available on the spatial coordinates. That is, GLCM and Invariant Moment use only the basic statistical techniques so reliability of the extracted features is low. In order to interpret the spatial relationship and weight of data, this study has used Principal Component Analysis [4,5] that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles.

• Journal of the Korean Society for information Management
• /
• v.23 no.2
• /
• pp.5-19
• /
• 2006

The purpose of this study is to observe and analyze information searching behaviors of various user groups in different access modes for designing user-centered query interface of content-based Music Information Retrieval System(MIRS). Two expert groups and two non-expert groups were recruited for this research. The data gathering techniques employed in this study were in-depth interviewing, participant observation, searching task experiments, think-aloud protocols, and post-search surveys. Expert users, especially majoring in music theory, preferred to input exact notes one by one using the devices such as keyboard and musical score. On the other hand, non-expert users preferred to input melodic contours by humming.

• The KIPS Transactions:PartD
• /
• v.14D no.6
• /
• pp.573-584
• /
• 2007

As multimedia information recently increases fast, various types of retrieval of multimedia data are becoming issues of great importance. For the efficient multimedia data processing, semantics based retrieval techniques are required that can extract the meaning contents of multimedia data. Existing retrieval methods of multimedia data are annotation-based retrieval, feature-based retrieval and annotation and feature integration based retrieval. These systems take annotator a lot of efforts and time and we should perform complicated calculation for feature extraction. In addition. created data have shortcomings that we should go through static search that do not change. Also, user-friendly and semantic searching techniques are not supported. This paper proposes to develop S-MARS(Semantic Metadata-based Multimedia Annotation and Retrieval System) which can represent and extract multimedia data efficiently using MPEG-7. The system provides a graphical user interface for annotating, searching, and browsing multimedia data. It is implemented on the basis of the semantic metadata model to represent multimedia information. The semantic metadata about multimedia data is organized on the basis of multimedia description schema using XML schema that basically comply with the MPEG-7 standard. In conclusion. the proposed scheme can be easily implemented on any multimedia platforms supporting XML technology. It can be utilized to enable efficient semantic metadata sharing between systems, and it will contribute to improving the retrieval correctness and the user's satisfaction on embedding based multimedia retrieval algorithm method.

• Journal of Information Science Theory and Practice
• /
• v.2 no.1
• /
• pp.6-21
• /
• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.47-50
• /
• 2001

This paper took advantage of SVD (Singular value Decomposition) techniques of LSI(Latent Semantic Indexing) to grasp easily terminology distribution. Existent LSI did to static database, propose that apply to dynamic database in this paper. But, if dynamic applies LSI to database, updating problem happens. Existent updating way is Recomputing method, Folding-in method, SVD-updating method. Proposed QR decomposition method to show performance improvement than existent three methods in this paper.

• Spatial Information Research
• /
• v.21 no.4
• /
• pp.83-89
• /
• 2013

Recently various contents have been produced using the techniques that require high-performance computing process. A lot of services have been being producted as AR(Augmented Reality) service being combined with mobile information service that a moving user search various information based on one's location with. Mobile information service has a characteristic that it needs to get new information according to the location an user moves to. The characteristic requires a lot of communications when user search information moving to a different location. In order to make up for this drawback, we propose a prefetching technique based on speed and viewing angle in this paper. Existing prefetching techniques retrieve the following location of users considering moving speed and direction of the users. The data showed on the screen in AR is limited by the viewing angle of the mobile device. Due to the problems we discussed above, existing prefetching techniques have a demerit that they retrieve a lot more data than needed actually. We propose more efficient way of retrieving data with AR using the viewing angle of the mobile device. The method we propose reduces retrieval of unnecessary location using the users' speed, direction and viewing angle. This method is more efficient than the existing ways of retrieval because we don't need as many data.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.12
• /
• pp.531-536
• /
• 2014

With the very large quantity of information available on the Internet, techniques for dealing with the abundance of documents have become increasingly necessary but the problem of processing information in the documents is still technically challenging and remains under study. Automatic document summary techniques have been considered as one of critical solutions for processing documents to retain the important points and to remove duplicated contents of the original documents. In this paper, we propose a document summarization technique that uses a fuzzy theory. Proposed summary technique solves the ambiguous problem of various features determining the importance of the sentence and the experiment result shows that the technique generates better results than other previous techniques.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.9-14
• /
• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.6
• /
• pp.1403-1408
• /
• 2010

Korean information retrieval uses noun as index terms or keywords of representing the document. and noun and keyword extraction is to find all nouns presented in the document, In this paper, we proposes the method of keyword extraction using pre-built dictionary. This method reduces the execution time by reducing unnecessary operations. And noun, even large documents without affecting significantly the accuracy, can be extracted. This paper proposed noun extraction method using the appearance characteristics of the noun and keyword extraction method using unsupervised learning techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.165-166
• /
• 2010

Noun extraction is to find all nouns presented in the document, Korean information retrieval uses noun as index terms or keywords of representing the document. In this paper, we proposes the method of keyword extraction using pre-built dictionary. This method reduces the execution time by reducing unnecessary operations. And noun, even large documents without affecting significantly the accuracy, can be extracted. This paper proposed noun extraction method using the appearance characteristics of the noun and keyword extraction method using unsupervised learning techniques.