• Journal of Information Processing Systems
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• v.7 no.2
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• pp.355-362
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• 2011

Since two-way interactive broadcasting service began, remote controls have been fitted with 4 color buttons, which enables interaction and convenience to increase between users and content. Currently, diverse studies on IPTV are in progress. Particularly, as the mobile market rapidly grows, studies on mobile IPTV and on linkage with other media are constantly increasing. However, mobile IPTV has never been studied until now. In that sense, this present study attempted to design a mobile-based IPTV UI that could use a multi-dimensional search method based on consistent criteria for content search. As a result, the proposed IPTV UI is fitted with more usability and functionality for 4 color buttons. The UI designed in this study was compared to the IMDb Android Application, which uses GOMS-KLM. The results showed that the performance process was reduced by three stages, and that the performance time was reduced by more than 17.9%. Therefore, the conclusion can be reached that the proposed UI is effective for a fast search of contents.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.96-101
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• 2010

The core study of semantic web is the efficiency of ontology parsing. The ontology parsing and inference is based on the significant information retrieval which is the ultimate purpose of semantic web. However, most existing ontology writing tools were not processing the efficient ontology parsing. Therefore, we design the two steps ontology parser for extracting the all facts, are included in the ontology, more fast in this study. In the first step, the token extractor collects the all tokens of ontology and the triple extractor extracts the statements in the collected tokens. In conclusion, we confirm that which is designed in this study, processes the ontology parsing more faster than the existing ontology parsers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.183-192
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• 2015

This paper proposes Personal Information Auto Detection(PIAD) System to prevent leakage of Personal informations in document and image files that can be used by mobile service provider. The proposed system is to automatically detect the images and documents that contain personal informations and shows the result to the user. The PIAD is divided into the selection step for fast and accurate retrieval images and analysis which is composed of SURF, erosion and dilation, FindContours algorithm. The result of proposed PIAD system showed more than 98% accuracy by selection and analysis steps, 267 images detection of 272 images.

• ETRI Journal
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• v.38 no.3
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• pp.518-528
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• 2016

The searching of an extensive document database for documents that are locally similar to a given query document, and the subsequent detection of similar regions between such documents, is considered as an essential task in the fields of information retrieval and data management. In this paper, we present a framework for such a task. The proposed framework employs the method of short-read mapping, which is used in bioinformatics to reveal similarities between genomic sequences. In this paper, documents are considered biological objects; consequently, edit operations between locally similar documents are viewed as an evolutionary process. Accordingly, we are able to apply the method of evolution tracing in the detection of similar regions between documents. In addition, we propose heuristic methods to address issues associated with the different stages of the proposed framework, for example, a frequency-based fragment ordering method and a locality-aware interval aggregation method. Extensive experiments covering various scenarios related to the search of an extensive document database for documents that are locally similar to a given query document are considered, and the results indicate that the proposed framework outperforms existing methods.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.357-364
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• 2005

In this paper, we propose an accurate and fast keyword spotting system for searching user-specified keyword in Hangul document images by using two-level image-to-image matching. The system is composed of character segmentation, creating a query image, feature extraction, and matching procedure. Two different feature vectors are used in the matching procedure. An experiment using 1600 Hangul word images from 8 document images, downloaded from the website of Korea Information Science Society, demonstrates that the proposed system is superior to conventional image-based document retrieval systems.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.41-48
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• 2008

This study focuses on the modeling file search engine and suggesting modified file search schema based on weight value using file contents in order to improve the performance in terms of search accuracy and matching time. Most of the file search engines have used string matching algorithms like KMP(Knuth.Morris.Pratt), which may limit portability and fast searching time. However, this kind of algorithms don't find exactly the files what you want. Hence, the file search engine based on weight value using file contents is proposed here in order to optimize the performance for mobile environments. The Comparison with previous research shows that the proposed schema provides better.

• Applied Microscopy
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• v.29 no.4
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• pp.493-498
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• 1999

With increasing demand for fast and reliable, yet economical data storage devices, the role of optical disk technology is becoming more important. In recent years, advanced laser technology combined with new materials has given the competitive edge over the traditional magnetic memory devices both in memory capacity and reliability of data retrieval. Continuing effort is being put into developing smaller and more complex structures for optical disks to increase their memory density. Characterization of such multilayered structure requires not only high spatial resolution for observation but also laborious specimen preparation. In this paper, the method of preparing optical disk specimens for TEM characterization is described in detail. The microstructural features in optical disks observed by TEM are also discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1044-1049
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• 2000

Projection that can be used as a feature for image representation, includes much available informations such as approximated shape and location. But when we retrieve image using it, there are some disadvantage such as requiring much index data and making different length of projected vector for differenr image size. In order to overcome these problems, we propose a method of using block variance for the projected vector. We use block variance of the projection vector to localize the characteristics of image and to reduce the number of index data in database. Proposed algorithm can make use of statistical advantage through database including various size of images and be executed with fast response time in implementation.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.601-605
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Millions of users have integrated these sites into their daily practices to communicate with online people. In this paper, we propose an efficient face annotation and retrieval system under SNS. Since the system needs to deal with a huge database which consists of an increasing users and images, both effectiveness and efficiency are required, In order to deal with this problem, we propose a face annotation classifier which adopts an online learning and social decomposition approach. The proposed method is shown to have comparable accuracy and better efficiency than that of the widely used Support Vector Machine. Consequently, the proposed framework can reduce the user's tedious efforts to annotate face images and provides a fast response to millions of users.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.51-56
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• 2009

In a language, noun and keyword extraction is a key element in information processing. When it comes to processing Korean language information, however, there are still a lot of problems with noun and keyword extraction. This paper proposes an effective noun extraction method that considers noun emergence features. The proposed method can be effectively used in areas like information retrieval where large volumes of documents and data need to be processed in a fast manner. In this paper, a category-based keyword construction method is also presented that uses an unsupervised learning technique to ensure high volumes of queries are automatically classified. Our experimental results show that the proposed method outperformed both the supervised learning-based X2 method known to excel in keyword extraction and the DF method, in terms o classification precision.