• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.345-348
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• 2005

Because the current web search engine estimates the similarity of documents, using the frequency of words, many documents irrespective of the user query are provided. To solve these kinds of problems, the semantic web is appearing as a future web. It is possible to provide the service based on the semantic web through ontology which specifies the knowledge in a special domain and defines the concepts of knowledge and the relationships between concepts. In this paper to search the information of potential customers for home-delivery marketing, we model the specific domain for generating the ontology. And we research how to retrieve the information, using the ontology. Therefore, in this paper, we generate the ontology to define the domain about potential customers and develop the search robot which collects the information of customers.

• ETRI Journal
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• v.32 no.5
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• pp.676-686
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• 2010

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real-world scenarios. In this paper, we propose a novel framework for mining high-utility sequential patterns for more real-life applicable information extraction from sequence databases with non-binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high-utility sequential patterns, we propose two new algorithms: UtilityLevel is a high-utility sequential pattern mining with a level-wise candidate generation approach, and UtilitySpan is a high-utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high-utility sequential patterns.

• International Journal of Knowledge Content Development & Technology
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• v.6 no.1
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• pp.41-68
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• 2016

This paper aims to analyze the function of database management systems from the perspective of librarians working in engineering institutions in Andhra Pradesh. Ninety-eight librarians from one hundred thirty engineering institutions participated in the study. The paper reveals that training by computer suppliers and software packages are the significant mode of acquiring DBMS skills by librarians; three-fourths of the librarians are postgraduate degree holders. Most colleges use database applications for automation purposes and content value. Electrical problems and untrained staff seem to be major constraints faced by respondents for managing library databases.

• Proceedings of the CALSEC Conference
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• 1999.07b
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• pp.607-614
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• 1999

In this paper, we demonstrate the implementation case using component based development tool under development process for application developments. The tool suggested provides the programming environment for the development of distributed manufacturing applications primarily. The development tool is classified into visual component, logic component, data component, knowledge component, neural net component, and service component which is a core component for the support component edit and execution. We applied the tool to the domain of the design and routing plan to retrieve existing similar design models in database, initiate a model, generate a process plan, and store the new model in the database automatically. Utilizing the tool, it integrates a geometric modeler, engineering/manufacturing database, and knowledge sources over the Internet.

• Journal of the Korean Society for Library and Information Science
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• v.34 no.4
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• pp.49-67
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• 2000

The purpose of this study is to suggest knowledge-based digital library model that is applicable in korea university library. This paper provides brief accounts of research and development trends of digital library in referring some major digital library projects that are in progress, or just completed. There follows a suggestion of eight essential modules for knowledge-based digital library system, that are infrastructure development of dissertation presentation and database construction, management and service of collections, infrastructure construction of journal service, development of unified viewer, database conversion, distributed & integrated retrieval system, cyber campus(private work space), and database connection.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.321-326
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• 2021

In a multi-cloud environment, it is necessary to minimize physical movement for efficient interoperability of distributed source data without building a data warehouse or data lake. And there is a need for a data platform that can easily access data anywhere in a multi-cloud environment. In this paper, we propose a new platform based on data fabric centered on a distributed platform suitable for cloud environments that overcomes the limitations of legacy systems. This platform applies the knowledge graph database technique to the physical linkage of source data for interoperability of distributed data. And by integrating all data into one scalable platform in a multi-cloud environment, it uses the holochain technique so that companies can easily access and move data with security and authority guaranteed regardless of where the data is stored. The knowledge graph database mitigates the problem of heterogeneous conflicts of data interoperability in a decentralized environment, and Holochain accelerates the memory and security processing process on traditional blockchains. In this way, data access and sharing of more distributed data interoperability becomes flexible, and metadata matching flexibility is effectively handled.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.269-277
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• 2000

The component reliability database is required in PSA (Probabilistic Safety Analysis) for NPP (Nuclear Power Plant). We have applied a generic database to the PSA for the Korean NPPs, since there is no specific component reliability database. Therefore we are developing the plant-specific component reliability database for domestic NPPs. We also extend the experience and knowledge of PSA and component reliability database for NPP to chemical industry We collect the raw data like component operation history and maintenance history and then input the required data for the component reliability database through failure analysis. With the database, we can not only perform PSA with real data but also perform maintenance optimization.

• Korean Management Science Review
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• v.18 no.1
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• pp.135-145
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• 2001

In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.4
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• pp.56-61
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skilful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workship, the other is the quantitative method which utilizes the experimental data obtained by a sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are now easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based model, which is strongly depended upon experience and intuition , is described.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.492-497
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• 1999

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skillful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop, the other is the quantitative method which utilizes the experimental data obtained by sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are not easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based rule, which is strongly depended upon experience and intuition, is described.