• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.41-56
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• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.347-357
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• 2003

The web is an important source of information and most of Web applications are based on form documents in HTML-based form documents only play a role as user interfaces, and they do not involve the procedures or rules if business process which form document designers assume. However, from documents imply methods for treating documents, and these embedded procedural knowledge can be utilized.actively in automation of business process. In this respect, we Investigate the activeness of documents with cognitive science to automate business processes based on from documents. Through this, we have a new concept and applicability of active documents. Our active documents include business rules and declarative knowledge to support the automation of document processing. Also, we propose a processing framework for the active documents. The framework has two phases: build-time and run-time. in order to demonstrate the usefulness of the proposed framework, a prototype called ActiveForm is designed and implemented for requisition processing them in an inference engine can enhance the intelligence of Internet applications.

• Journal of KIISE
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• v.42 no.10
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• pp.1195-1206
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• 2015

For the management of a knowledge system, systems that automatically infer and manage scalable knowledge are required. Most of these systems use ontologies in order to exchange knowledge between machines and infer new knowledge. Therefore, approaches are needed that infer new knowledge for scalable ontology. In this paper, we propose an approach to perform rule based reasoning for scalable SHIF ontologies in a spark framework which works similarly to MapReduce in distributed memories on a cluster. For performing efficient reasoning in distributed memories, we focus on three areas. First, we define a data structure for splitting scalable ontology triples into small sets according to each reasoning rule and loading these triple sets in distributed memories. Second, a rule execution order and iteration conditions based on dependencies and correlations among the SHIF rules are defined. Finally, we explain the operations that are adapted to execute the rules, and these operations are based on reasoning algorithms. In order to evaluate the suggested methods in this paper, we perform an experiment with WebPie, which is a representative ontology reasoner based on a cluster using the LUBM set, which is formal data used to evaluate ontology inference and search speed. Consequently, the proposed approach shows that the throughput is improved by 28,400% (157k/sec) from WebPie(553/sec) with LUBM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.666-677
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• 2015

The importance of application traffic analysis for efficient network management has been emphasized continuously. Snort is a popular traffic analysis system which detects traffic matched to pre-defined signatures and perform various actions based on the rules. However, it is very difficult to get highly accurate signatures to meet various analysis purpose because it is very tedious and time-consuming work to search the entire traffic data manually or semi-automatically. In this paper, we propose a novel method to generate signatures in a fully automatic manner in the form of sort rule from raw packet data captured from network link or end-host. We use a sequence pattern algorithm to generate common substring satisfying the minimum support from traffic flow data. Also, we extract the location and header information of the signature which are the components of snort content rule. When we analyzed the proposed method to several application traffic data, the generated rule could detect more than 97 percentage of the traffic data.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.417-419
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• 2012

국내의 자동차 정비 훈련 교육 현장에는 훈련교사가 빠르게 발전되고 있는 자동차 정비 기술 수준에 맞춰 교육하는데 어려움이 있다. 이 같은 어려움을 해결하기 위한 이-트레이닝(E-training) 시스템은 체험형 훈련이 가능하면서도 높은 학습 효과를 가져올 것이라 기대되고 있다. 자동차 정비 훈련을 위한 이-트레이닝 시스템은 훈련교사가 자동차 고장 항목을 설정하면, 훈련생이 고장 진단을 위한 다양한 시도를 하여 고장을 인지하고, 그에 따른 조치를 통해 주어진 문제를 해결함으로써 학습효과가 높아질 것이라 기대되는 시스템이다. 하지만 이-트레이닝 시스템은 이미 설정되어 있는 시나리오에 따른 일방적인 교육, 학습자에 대한 지속적인 관리의 어려움, 학습자의 행동을 추론하여 정확한 결과를 도출해내기가 어렵다는 한계가 있다. 본 논문에서는 이-트레이닝 시스템의 문제점을 해결하기 위한 방법으로 자동차 정비를 위한 자동차 몸체, 엔진, 정비 도구에 대한 온톨로지를 구축하고 추론하여 효과적인 자동차 정비 훈련 교육이 될 수 있도록 하는 방법을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.247-250
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• 2020

현재 전개되고 있는 대부분의 인터랙티브 사이니지는 SI 작업으로, 해당 응용 및 적용 현장에 맞게 하드코딩을 하여 고정된 방식으로 구현되고 있다. 따라서, 또 다른 현장의 응용 목적 사이니지 개발을 위해 다시 엔지니어가 재프로그래밍하여야 하는 불편 및 낭비가 존재한다. 본 논문에서는 안드로이드 사이니지 플레이어 환경에서의 더욱 유연하게 확장되고 개선된, 상황인지 지원 안드로이드 인터랙티브 사이니지 시스템 설계와 구현에 대한 개발 결과를 보고한다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.40-49
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• 2009

HAO is a ORB engine to support the logic-based CORBA development environments in FPGA. In this papers, in order to support the logic component developments with HAO, we proposes the translation rule from IDL to VHDL, and the generation of skeleton logic code following the rule. It enables to guarantee the interoperability between the components in distributed multi processor environments includes the general purpose processor and FPGAs, and to improve the performance through the usage of logic-circuit.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.4
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• pp.205-214
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• 2010

BPEL is a standard workflow language, which interacts with Web Services and is used in various applications. But it is difficult to use BPEL for specific applications which require additional functions. In this paper, we present a system which can add new functions to BPEL based on an aspect-oriented programming (AOP) technique. In order to add new functions to BPEL, we define a JWX document format that can describe new functions to apply to BPEL. JWX is XML-oriented document that can code the corresponding Java program in order to dynamically add new functions to BPEL documents. It is possible for BPEL workflow to add new functions without modifying the existing programs using the AOP technique, which guarantees low degree of coupling between key and additional requirements. Additionally this systems weaves based on new functions of Java program and JWX document by expanding BPEL engine called B2J based on AOP and execute them. Therefore it is possible to develop a new BPEL engine with additional functions easily and with low cost. The new system can execute additional conditions that the current BPEL engine doesn’t provide. The new system using functions of BPEL supplied by B2J. The new system can be used to add a new rule engine, which isn't currently provided.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.