• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.87-99
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• 2009

The top-down method for SOA delivery is recommended as a best way to take advantage of SOA. The core step of SOA delivery is the step of service modeling including service analysis and design based on ontology. Most enterprises know that the top-down approach is the best but they are hesitant to employ it because it requires them to invest a great deal of time and money without it showing any immediate results, particularly because they use well-defined component based systems. In this paper, we propose a service identification method to use a well-defined components maximally as a bottom-up approach. We assume that user's inputs generates events on a GUI and the approximate business process can be obtained from concatenating the event paths. We first find the core GUIs which have many outgoing event calls and form event paths by concatenating the event calls between the GUIs. Next, we adapt sequential pattern mining algorithms to find the maximal frequent event paths. As an experiment, we obtained business services with various granularity by applying a cohesion metric to extracted frequent event paths.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.6-19
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• 2024

The Korean Archaeological Dictionary, which represents Korean archaeological knowledge information, contains refined and high-quality information written by expert collective intelligence. This is a characteristic that clearly distinguishes it from overseas archaeological data archives, and can be called differentiated infrastructure data. However, it has not played a role as an information service or knowledge information platform reflecting the latest digital technology. As a way to maximize these strengths and compensate for weaknesses, it was proposed to develop and operate a GIS-based knowledge and information platform for Korean archaeology. To realize this, it is necessary to develop a title management system centered on repositories and metadata that can collect and store various information, link open linked data design and related systems, develop a search function that can analyze and visualize data in response to the big data era, and establish a WebGIS-based information service system. This will be a platform to continuously manage, supplement, and update Korean archaeological knowledge information, build a ubiquitous environment where anyone can use information anytime, anywhere, and create various types of business models.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.418-424
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• 2014

This paper aim; to develop the National R&D Information Navigation System(NRnDINS) that is convenient and easy to use by the researchers on the basis of information filtering and visualization by converging and integrating the three types of the contents, namely, paper, report and project at the stage of development of the information system An information system is developed by establishing ontology and RDF on the three types of contents, and by applying information filtering and semantic search technology after having created the prototype for the screen by reflecting the user needs analysis and information visualization elements surveyed at the previous stage of information service planning. In this paper, to make the measure for information filtering, R&D navigation index is prosed and implemented, and NRnDINS capable of integrated search of the R&D contents through information visualization is developed. Also, for the testing of the developed system, the preference survey for its design by 1m persons and usability test of the system by 10 users are performed The result of the survey on the preference for the design is affirmative with 85% of the subjects finding it favorable and the composite receptivity is good with the score of 87.2 the results of the usability test. However, it was also found that further development of the personalization functions is needed. It is hoped that the R&D navigation index of the proposed and implemented in this paper would present quantitative objectivity and will induce further development of other information filtering index of contents in the future.

• Spatial Information Research
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• v.18 no.2
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• pp.67-75
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• 2010

When people are shopping at a large shopping mall, they usually become to go around many stores for looking for better products and comparing them. In this paper, we design and implement a purchasing activity support system based on an Ambient Service Model that provides relevant stores information on map interface hierarchically through user contexts based search, to support such user's purchasing activities with the help of relevant information. In this system, users can search for relevant stores information through the system by Ambient Query which is created by their location and stores information with a mobile device. Then, users obtain relevant stores information provided in the form of hierarchy of keywords as a highly condensed summary and easily figure out the locations of the stores on a map interface. Moreover, users search additional other kinds of relevant stores information over the hierarchy of keywords. Eventually, users can obtain relevant stores information intuitively and conveniently without complex search processes. We implemented this system by integrating the subordinate technologies such as RFID, map-based, location-based and ontology technology. We also performed experiments on a well-known shopping region (Ilsan Lapesta shopping mall, Goyang-city Gyeonggi-do, Korea). Finally, we also confirmed that users' shopping activities were significantly improved by utility the present system.

• Journal of KIISE
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• v.42 no.8
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• pp.998-1009
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• 2015

In recent years, there has been a growing interest in RDFS Inference to build a rich knowledge base. However, it is difficult to improve the inference performance with large data by using a single machine. Therefore, researchers are investigating the development of a RDFS inference engine for a distributed computing environment. However, the existing inference engines cannot process data in real-time, are difficult to implement, and are vulnerable to repetitive tasks. In order to overcome these problems, we propose a method to construct an in-memory distributed inference engine that uses a parallel graph structure. In general, the ontology based on a triple structure possesses a graph structure. Thus, it is intuitive to design a graph structure-based inference engine. Moreover, the RDFS inference rule can be implemented by utilizing the operator of the graph structure, and we can thus design the inference engine according to the graph structure, and not the structure of the data table. In this study, we evaluate the proposed inference engine by using the LUBM1000 and LUBM3000 data to test the speed of the inference. The results of our experiment indicate that the proposed in-memory distributed inference engine achieved a performance of about 10 times faster than an in-storage inference engine.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.637-648
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• 2009

As the cost of disks decreases, PCs are soon expected to be equipped with a disk of 1TB or more. Assuming that a single person generates 1GB of data per month, 1TB is enough to store data for the entire lifetime of a person. This has lead to the growth of researches on lifelog management, which manages what people see and listen to in everyday life. Although many different lifelog management systems have been proposed, including those based on the relational data model, based on ontology, and based on file systems, they have all advantages and disadvantages: Those based on the relational data model provide good query processing performance but they do not support complex queries properly; Those based on ontology handle more complex queries but their performances are not satisfactory: Those based on file systems support only keyword queries. Moreover, these systems are lack of support for lifelog group management and do not provide a convenient user interface for modifying and adding tags (metadata) to lifelogs for effective lifelog search. To address these problems, we propose a lifelog management system based on the relational data model. The proposed system models lifelogs by using the relational data model and transforms queries on lifelogs into SQL statements, which results in good query processing performance. It also supports a simplified relationship query that finds a lifelog based on other lifelogs directly related to it, to overcome the disadvantage of not supporting complex queries properly. In addition, the proposed system supports for the management of lifelog groups by providing ways to create, edit, search, play, and share them. Finally, it is equipped with a tagging tool that helps the user to modify and add tags conveniently through the ion of various tags. This paper describes the design and implementation of the proposed system and its various applications.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.43-57
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• 2015

In this thesis was conducted to propose a method for efficient information retrieval using concept lattices. Since this thesis designed a new system based on ordinary concept lattices, it has the same approach method as ontology, but this thesis proposes new concept lattices to be used by establishing collaborative relations between objects and concepts that users are likely to search information more efficiently. The system suggested by this thesis can be summarized as below. Firstly, this system leads to a collaborative search by using Three kinds of concepts, such as keyword concept lattices, which focus on input key words, expert concept lattices recommended by experts and theme concept lattices, and based on these 3 concept lattices, it will help users search information they want more efficiently. Besides, as the expert concept and the keyword concept become combined, further providing users with the frequency of keyword and the frequency of category, this system can function to recommend key words related to search words entered by users. Another function of this system is to inform users of key words and categories used in users' interested themes by using the theme concept lattices. Secondly, when there is not keyword entered by a user, it is possible for users to achieve the goal of search through the secondary search when this system provides them with key words related to the input keyword. Thirdly, since most of the information is managed while being dispersed, such dispersed and managed information not only has different expression methods but changes as time goes. Accordingly, By using XMDR for efficient data access and integration of distributed information, this thesis proposes a new technique and retrieval system to integrate dispersed data.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.187-199
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• 2009

With the advent of Web 2.0, OpenAPIs are becoming an increasing trend to emphasize Web as platform recently. OpenAPIs are used to combine services and generate new services by mashup. However because the standard documents for OpenAPIs do not exist, it may restrict the use of OpenAPIs. Previous studies of OpenAPIs mashup have been limited to tool design or language definition for service combination rather than dynamic composition. On the other hand, Web services that are a software technology implementing SOA provide standard documents such as WSDL to explain each service, UDDI to register it, and SOAP to transfer messages. Thus Web applications can interpret and execute services by using these technologies. Recent works have also been performed to provide semantic features and dynamic composition for SOA. If a dynamic and systematic approach is provided to combine Web services and OpenAPIs, Web applications can provide users with diverse services. In this study, we present a SOA based framework for mashup of OpenAPIs and Web services. The framework supports dynamic composition of OpenAPIs and Web services, where the process of composite services is described in OWL-S. A prototype is provided to validate our framework. The framework is expected to add diversity to typical Web services.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.159-168
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• 2012

Relation in the new IT environment, such as the SNS, Cloud, Web3.0, has become an important factor. And these relations generate a transaction. However, existing relational database and graph database does not processe graph structure representing the relationships and transactions. This paper, we propose the technique that can be processed concurrently graph structures and transactions in a scalable complex network system. The proposed technique simultaneously save and navigate graph structures and transactions using the Topic Maps data model. Topic Maps is one of ontology language to implement the semantic web(Web 3.0). It has been used as the navigator of the information through the association of the information resources. In this paper, the architecture of the proposed technique was implemented and design using Cassandra - one of column type NoSQL. It is to ensure that can handle up to Big Data-level data using distributed processing. Finally, the experiments showed about the process of storage and query about typical RDBMS Oracle and the proposed technique to the same data source and the same questions. It can show that is expressed by the relationship without the 'join' enough alternative to the role of the RDBMS.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.618-632
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• 2005

A framework for semantic annotation oi human motion sequences is proposed in this paper. Motion capture technology is widely used for manuiacturing animation since it produces high qualify character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. It is difficult for animators to retrieve the desired motion sequences from motion capture files as there is no semantic annotation on already captured motion data. Our goal is to improve the reusability of motion capture data. To archive our goal first, we propose a standard format for integrating different motion capture file formals. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (extensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents Second, we define motion ontologies that are used to annotate and semantically organize human motion sequences. This ontology-based approach provides the means for discovering and exploiting the information and knowledge surrounding motion capture data.