• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.132-144
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• 2017

The fingerprint classification of categorizing fingerprints by classes should be used in order to improve the processing speed and accuracy in a fingerprint recognition system using a large database. The fingerprint classification methods extract features from the fingerprint ridges of a fingerprint and classify the fingerprint using learning and reasoning techniques based on the classes defined according to the flow and shape of the fingerprint ridges. In earlier days, many researches have been conducted using NIST database acquired by pressing or rolling finger against a paper. However, as automated systems using live-scan scanners for fingerprint recognition have become popular, researches using fingerprint images obtained by live-scan scanners, such as fingerprint data provided by FVC, are increasing. And these days the methods of fingerprint classification using Deep Learning have proposed. In this paper, we investigate the trends of fingerprint classification technology and compare the classification performance of the technology. We desire to assist fingerprint classification research with increasing large fingerprint database in improving the performance by mentioning the necessity of fingerprint classification research with consideration for fingerprint images based on live-scan scanners and analyzing fingerprint classification using deep learning.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.356-366
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• 2021

The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.229-249
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• 2016

This study was conducted to create a digital archive for local cultural contents compiled from the records of westerners who stayed in Korea during the Enlightenment Period of Chosun. The compiled information were gathered from 22 records, and 10 main subjects, 40 sub-subjects and 239 mini-subjects were derived through the subject classification scheme. Item analysis was conducted through 38 metadata and input data types were classified and databased in Excel. Finally, a web-based digital archiving system was developed for searching and providing information through various access points. Suggestions for future research were made to expand archive contents through continuous excavation of westerners' records, to build an integrated information system of Korean digital archives incorporating individual archive systems, to develop standardization of classification schemes and a multidimensional classification system considering facet structure in cultural heritage areas, to keep consistency of contents through standardization of metadata format, and to build ontology using semantic search functions and data mining functions.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.62-64
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• 2004

P2P Systems have grown dramatically in recent years. Now many P2P systems have developed and been confronted by P2P technical challenges. We should consider how to efficiently locate desired resources. In this paper we integrated the existing pure P2P and hybrid P2P model. We try to keep roles of super peer in hybrid and concurrently use pure P2P model for searching resource. In order to improve the existing search mechanism, we present contents-based classification mechanism. Proposed system have the following features. This can forward only query to best peer using RI. Second, it is self-organization. A peer can reconfigure network that it can communicate directly with based on best peer. Third, peers can cluster each other through contents-based classification.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.867-875
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• 2009

More and richer information sources and services are available on the web everyday. However, harmful information, such as adult content, is not appropriate for all users, notably children. Since internet is a worldwide open network, it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse ways, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies and examine which algorithms for feature selection, the process that select content terms, as features, can be useful for text categorization in all content term occurs in documents, are suitable for classifying harmful contents through implementation and experiment.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.543-547
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• 2006

Recently domestic companies have been needed to securing competitive techniques due to increasing orders of plant industries in the oversea construction market. Although domestic engineering companies have been assessed competitive in the field of detail design, their high value-added basic design have evaluated uncompetitive. To manage efficiently various contents which occurred in works of design steps, the management method must be built. In this study, we have found the contents which required to management through the definition of main works and analysis of characteristics in the step of basic design. Then, we have suggested to Contents Classification System which reflected of work flows and relations among stakeholders. Proposed Contents Classification System will help us when requiring the proper documents, drawings, sheets and other information.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.181-189
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• 2003

The requirement of distributed multimedia applications is the need for sophisticated QoS(quality of service) management. In terms of distributed multimedia systems, the most important catagories for quality of service are a timeless, volume, and reliability In this paper, we discuss a method for increasing reliability through fault tolerance. We describe the design and implementation of the ECA running on distributed multimedia environment. ECA is a system is able to classify automatically a software error based on distributed multimedia. This papaer explains a performance analysis of an error classification system running on distributed multimedia environment using the rule-based DEVS modeling and simulation techniques. In DEVS, a system has a time base, inputs, states, outputs, and functions.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.27-40
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• 2023

With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.181-191
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• 2016

We analyzed the search word of the media content in the IPTV service, and as a result we found that an important factor is general meta information as well as content(material, plot, etc.) and emotion information in the media content selection criteria of customers. Therefore, in this research, in order to efficiently provide various media contents of IPTV to users, we designed the emotion classification system for utilizing the emotion information of the media content. Next, we proposed 'personalized media contents curation system based on emotion information' for organizing the media contents, through the various processing steps. Finally, to demonstrate the effectiveness of this system, we conducted a user satisfaction survey(72.0 points). In addition, the results of comparing the results based on popularity and the results of the proposed system showed that the ratio leading to the actual users' viewing behavior was 10 times higher.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.245-248
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameter data base for the audio data to implement the audio data index and searching system. Audio data is classified to the primitive various auditory types. We described the analysis and feature extraction method for the feature parameters available to the audio data classification. And we compose the feature parameters data base in the index group unit, then compare and analyze the audio data centering the including level around and index criterion into the audio categories. Based on this result, we compose feature vectors of audio data according to the classification categories, and simulate to classify using discrimination function.