• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.643-648
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• 2003

In order to provide efficient retrieving results for user query on the web environment, the various searching algorithms have developed and considered user's preference and convenience. However, the searching algorithms are developed on the horizontal and non hierarchical web environment in general and could not apply to the complex hierarchical and functional web environments such like the enterprise network. In this paper, we purpose the multi-agent based web mining system which can provide the efficient mining results to the user on the special web environment. For doing this, we suggest the network model with the hierarchical web environment and model the multi agent based web mining system which has four corporation agents and fourteen process modules. Then, we explain the detailed functions of each agent considered the hierarchical environment according to the module. Especially, we purpose the new merging agent and improved ranking algorithm by using the graph theory.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.39-44
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• 2011

Recently, due to people's incontinent use all over the world, fossil fuels such as coal, oil, and natural gas were nearly to be exhausted and also causes serious environment pollutions. Therefore, there is a strong need to develop solar, wind, hydro, biomass, geothermal to replace fossil fuels to prevent suffering from above problems. Wish advances in sensor technology, such data is collected as a kind of stream data which arrives in an online manner so that it is characterized as high- speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. Therefore, the traditional data processing techniques are not fit to deal with stream data. In this paper, we propose a kalman filter-based algorithm to process renewable stream data.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.23-37
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• 1994

In this paper, we design and implement the prototype system, and propose the Extended Faceted Classification. Scheme and the Hybrid Retrieval Method that support classifying the software components, storing in library, and efficient retrieval according to user's request. In order to designs the classification scheme, we identify several necessary items by analyzing basic classes of software components that are to be classified. Then, we classify the items by their characteristics, decide the facets, and compose the component descriptors. According to their basic characteristics, we store software components in the library by clustering their application domains and are assign weights to the facets and its items to describe the component characteristics. In order to retrieve the software components, we use the retrieval-by-query model, and the weights and similarity for easy retrieval of similar software components. As the result of applying proposed classification scheme and retrieval model, we can easily identify similar components and the process of classification become simple. Also, the construction of queries becomes simple, the control of the size and order of the components to be retrieved possible, and the retrieval effectiveness is improved.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1443-1452
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• 1996

In this paper, we propose a semantic similarity measure for reusable software components, which aims to provide the automatic classification process of reusable to be stored in the structure of a software library, and to provide an efficient retrieval method of the software components satisfying the user's requirements. We have identified the facets to represent component characteristics by extracting information from the component descriptions written in a natural language, composed the software component identifiers from the automatically extracted terms corresponding to each facets, and stored them which the components in the nearest locations according to the semantic similarity of the classified components. In order to retrieve components satisfying user's requirements, we measured a semantic similarity between the queries and the stored components in the software library. As a result of using the semantic similarity to retrieve reusable components, we could not only retrieve the set of components satisfying user's queries. but also reduce the retrieval time of components of user's request. And we further improve the overall retrieval efficiency by assigning relevance ranking to the retrieved components according to the degree of query satisfaction.

• The Transactions of the Korea Information Processing Society
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• v.1 no.3
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• pp.299-310
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• 1994

Re-engineering tools can substantially increase software maintenance productivity and the quality of maintenance work. Re-engineering usually involves changing the form(e.g.changining objects names and definitions, restructuring process logic) of a program. In this paper, we describe the design and implementation of InMaC＋＋ that is a software tool oriented towards maintenance of C＋＋ object oriented programs. With InMaC＋＋, programms can be displayed and edited in two forms : as the code and as the diagram InMaC＋＋ also contains transformations in both directions, i,e. from code to diagram and from diagram to skeletons of code. Hence, it is suitable for re-engineering and maintenance of existing code. Specially designed browsers implement the graphical interface. InMaC＋＋ contains a database that is based on a simple but effective data model of InMaC＋＋ programs. The model contains only four object classes and three relations, which makes the tool small, and easy to implement and use. A simple query language allows browsing through the database.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.349-362
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• 1997

In order to make a meaningful multi-media object,it is usually necessary to apply a number of non-trival operations.If multi-media data can be encapsulated in a standaridized form and stored in a database,it is poss-ible to share and reuse multi-media data among users without repeating the same or similar operations. Based on the OLE component object model,this paper proposes the integrated computing enviroment for naive user to share and reuse of Ole objects.Various types of multi- media objects that are created by their appropriate OLE application programs can be aggreagated to form a multi-media document.In addition,the OLE objects can also be stored in database by a controlled manner.TheOLE object in a database can be retrieved by a visual query interface and reused to make a new document.This paper describes the common Platform to integrate various ment of OLE appfication programs,the separation process of an OLE object form a document,and the overall management of OLE object in a database.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.135-145
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• 2011

These days, the research of a sensor data management system for USN based real-time monitoring application is active thanks to the development and diffusion of sensor technology. The sensor data is rapidly changeable, continuous and massive row level data. However, end user is only interested in high level data. So, it is essential to effectively process the row level data which is changeable, continuous and massive. In this paper, we propose a sensor data management system with multi-analytical query function using OLAP and anomaly detection function using learning based classifier. In the experimental section, we show that our system is valid through the some experimental scenarios. For the this, we use a sensor data generator implemented by ourselves.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.53-63
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• 2011

Many techniques have been proposed to store and query XML data efficiently. One way achieving this goal is using relational database by transforming XML data into relational format. It is important to transform schema to preserve the content, the structure and the constraints of the semantics information of the XML document. Especially, key constraints are an important part of database theory. Therefore, the proposal technique has considered the semantics of XML as expressed by primary keys and foreign keys. And, the proposal technique can preserve not only XML data constraints but also the content and the structure and the semantics of XML data thru transformation process. Transforming information is the content and the structure of the document(the parent-child relationship), the functional dependencies, semantics of the document as captured by XML key and keyref constraints. Because of XML schema transformation ensures that preserving semantic constraints, the advantages of these transformation techniques do not need to use the stored procedure or trigger which these data ensures data integrity in the relational database. In this paper, there is not chosen the ID/IDREF key which supported in DTD, the inheritance relationship, the implicit referential integrity.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.537-542
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• 2015

Database Shard is a technique that can be queried and stored by dividing one logical table into multiple databases horizontally. In order to analyze the shard data with aggregate or analysis functions, a process is required that integrates partial results on each shard database. In this paper, we introduce the design and implementation of a distributed processing system for aggregation and analysis on the CUBRID Shard distributed database, which is an open source database management system. The implemented system can accelerate the analysis onto multiple shards of partitioned tables; it shows efficient aggregation on shard distributed databases compared to stand-alone databases.