• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.285-307
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• 2009

This paper introduces DICE, a Domain-Independent text Classification Engine. DICE is robust, efficient, and domain-independent in terms of software and architecture. Each module of the system is clearly modularized and encapsulated for extensibility. The clear modular architecture allows for simple and continuous verification and facilitates changes in multiple cycles, even after its major development period is complete. Those who want to make use of DICE can easily implement their ideas on this test bed and optimize it for a particular domain by simply adjusting the configuration file. Unlike other publically available tool kits or development environments targeted at general purpose classification models, DICE specializes in text classification with a number of useful functions specific to it. This paper focuses on the ways to locate the optimal states of a practical text classification framework by using various adaptation methods provided by the system such as feature selection, lemmatization, and classification models.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.401-425
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• 2009

This study is intended to present methods improving the classification system of KDC architecture engineering fields after comparing and analyzing the academic system of architecture engineering, classification system of KDC, DDC, and LCC, and that of the research field classification system of National Research Foundation of Korea. The results of the analysis have revealed that it is required to improve and correct the KDC 5th edition of architectural engineering including the addition of classification items that reflect the trend of academic development, proper development in the rank classification terms of architectural structure engineering, addition of detailed subjects, selection of proper classification terms, errors of classification symbols and English expression, and omission of correlative indexes in the classification items. This study has proposed improved methods to solve those problems.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.151-165
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• 2009

Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of its outstanding accuracy of control and forecasting area. We design a new classification model based on ANFIS and evaluate it in terms of classification accuracy. We identified ANFIS-based classification model has higher classification accuracy compared to existing classification model, C5.0 decision tree model by comparing their experimental results.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.135-171
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• 2014

The aim of this study was to suggest a classification system adapted to provide policy information services. For this purpose, this study completed the following processes; BRM taxonomy analysis, document analysis, analysis of classification systems providing policy information, consulting classification experts, surveys and interviews with policy information consumers, and an empirical validation process through the actual construction of policy information materials. Finally, this study complemented and modified the BRM taxonomy system and proposed a classification system appropriate to policy information resources. Through the procedures of experts discussion, the steps of BRM analysis appropriate to provide policy information services is determined as three steps. The domestic institute websites for policy information services has confirmed the appropriateness of the BRM taxonomy system through the analysis system and service research to provide policy information resources. Also through the specialist interview, the confirmation of BRM and the improvement has been drawn. Through the questionaires, the study analyzes the appropriateness of available BRM taxonomy system and the requirements by subjects. And through the empirical verificaion, it determines the subject of BRM taxonomy system for policy information services.

• Korean Journal of Construction Engineering and Management
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• v.4 no.3 s.15
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• pp.102-111
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• 2003

It is very important to improve the overall efficiency in exchanging construction information among project Parties from the project set-up through the project completion. However, each government agency in Korea tendering construction projects has different structures in classifying information. This results in inefficiency of overall construction projects and cost increasing. This requires establishing a new construction information classification system. This research suggests a framework for an analysis of a standard classification system in setting up a standard classification system and in evaluating its applicability to business processes. According to the identified requirements of the classification system, this research analyzes and compares existing information classification systems such as Uniclass, Uniformat, and Korean Standard Classification System of Construction Information, and then identifies problems and approaches for the improvement.

• 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 Society of Disaster Information
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• v.14 no.1
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• pp.28-35
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• 2018

The following research has focused and implemented on designing a system that classifies the severity of mass casualty situations across both normal and disaster levels. The system's algorithm has implemented requirements such as accuracy as well as user convenience. The developed e-Triage System has applied various severity classification algorithms implemented from IoT concepts. In order to overcome flaws of currently used severity classification systems, the e-Triage System used electronic elements including the NFC module. By using the mobile application's severity classification algorithm the system demonstrated quick and accurate assessment of patient. Four different LED lamps visualized the severity classification results and RTS scores were portrayed through FND(Flexible Numeric Display) after a two wave classification.

• Journal of Korean Library and Information Science Society
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• v.41 no.4
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• pp.5-33
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• 2010

This study is intended to present methods improving the classification system of KDC education fields after comparing and analyzing the academic system of education, classification system of KDC, NDC, DDC and LCC, and that of the research field classification system of National Research Foundation of Korea. The results of the analysis have revealed that it is required to improve and correct the KDC 5th edition of education including the addition of classification items that reflect the trend of academic development, proper development in the rank classification terms of education detailed fields, addition of detailed subjects, errors of classification symbols and omission of correlative indexes in the classification items. This study has proposed improved methods to solve those problems.

• Journal of Korean Library and Information Science Society
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• v.48 no.2
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• pp.373-403
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• 2017

The purpose of this study is to establish the classification principle of archives for the May 18th democratic uprising in terms of preservation and utilization of it and to develop an integrated classification system for it. For this purpose, it was carried out by the previous research on the classification of records and institutional case analysis. Also, we developed an integrated provenance-based classification system based on the practical analysis on the data held in 3 representative institutions in Gwangju. This classification system was proposed by facets of 'provenance-material-period-media-subject' type. We also proposed the collection-based integrated classification system that reflects on the expansion of archivists' role and the trend of times.