• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.152-157
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• 2006

상황 정보 관리 시스템은 외부에서 입력된 상황 정보의 숨겨진 의미를 파악하여 상황인지 에이전트 및 상황인지 브로커가 효과적으로 상황정보를 획득하도록 한다. 본 논문에서는 외부 환경으로부터 받은 상황정보의 숨겨진 의미를 파악하기 위해 DL 추론과 시간적 추론을 적용한 상황 정보 관리 시스템을 제안한다. 이를 위해서 3가지 부분에 초점을 두었다. 첫 번째, 외부에서 입력된 상황 정보를 효율적으로 표현하고 여러 에이전트간의 상황 정보 공유가 가능하도록 온톨로지 모델을 적용한다. 온톨로지로 표현된 상황정보는 정보의 속성을 제약함으로써 숨겨진 상황 정보를 추론할 수 있도록 해준다. 두 번째로 상황 정보의 관계를 추론할 수 있도록 서술 논리(Description Logic)를 적용한다. 마지막으로 상황 정보의 시간적 관계를 추론할 수 있도록 시간 논리(Temporal Logic)을 적용한다. 따라서 본 논문에서의 최종 목표는 상황 정보 관리 시스템 연구를 통해 상황인지 에이전트 및 상황인지 브로커에 활용이 가능한 온톨로지 기반 추론 기능을 보유하는 지능형 모듈의 기본 프레임워크를 구축하는 것이다.

• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.411-419
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• 2009

In order to derive hidden Information (concept subsumption, concept satisfiability and realization) of OWL ontologies, a number of OWL reasoners have been introduced. Most of the reasoners were implemented to be based on tableau algorithm. However this approach has certain limitation. This paper presents architecture for Medusa. The Medusa is an extended DL-reasoner for SWRL(Semantic Web Rule Language) reasoning under well-founded semantics with ontologies specified in Description Logic. Description logic based ontology reasoners theoretically explore knowledge representation and its reasoning in concept languages. However these logics are not equipped with rule-based reasoning mechanisms for assertional knowledge base; specifically, rule and facts in logic programming, or interaction of rules and facts with terminology. In order to deal with the enriched reasoning, The Medusa provides combining DL-knowledge base and rule based reasoner. The described prototype uses $Prot{\acute{e}}g{\acute{e}}$ API[1] for controlling communication with the ontology reasoner.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.530-538
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• 2007

Most existing deductive engines study for optimization of TBox based on Tableaux algorithm. However, in order to deduce mass-storing ABox in reality, it can't be decided in finite time. Therefore, for the efficiency of the deductive engine, there needs to be reasoning technique optimized for ABox. This paper uses the method that changes OWL-DL based Ontology to the form of Rule like Datalog in order to interlock store device such as RDBMS. Ultimately, it tries to in circumstance of real world. Therefor, using Axiom that OWL holds, it suggests reasoning method that applies rules including datatype.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.29-45
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• 2015

This paper proposes an implementation of SPARQL-DL, which is a query language for OWL ontologies, for query-answering over the OWL ontologies virtually generated from existing RDBs. The proposed SPARQL-DL processor internally translates input SPARQL-DL queries into SQL queries and then executes the translated queries. There are two advantages in the query processing method. First, another repository to store OWL ontologies generated from RDBs is not required. Second, a large ABox generated from an RDB instance is able to be served without using Tableau algorithm based reasoners which have a problem in large ABox reasoning. Our algorithm for query rewriting is designed to create one corresponding SQL query from one input SPARQL-DL query to minimize the overhead by establishing connections with RDBs.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.655-666
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• 2007

Reasoners using typical Tableaux algorithm such as RacerPro, Pellet have a problem in Tableaux algorithm large ABox reasoning. Researches to solve these Problems are dealt with Instance Store of University of Manchester which uses Tableaux algorithm based reasoner and DBMS and KAON2 of University of Karlsruhe using Disjunctive Datalog approach. An evaluation experiment for present reasoners is the experiment of TBox reasoning in most of Tableaux algorithm based one. The most of benchmarking tests in reasoning systems haven't done with ABox reasoning based Tableaux Algorithm but done with TBox reasoning based Tableaux Algorithm. Especially, rarely reported benchmarking tests in reasoners have been issued nowadays. Therefore, this thesis evaluates systems with theory of each reasoners for large ABox reasoning that becomes issues recently with typical reasoners. The large AoBx reasoning engine will be analyzed using Instance Store and KAON2 of Manchester University for large ABox processing. At the analysing method, LUBM(Lehigh University BenchMark), benchmarking test method, and it's test system will be introduced. In conclusion, I recommend appropriate reasoner in various environment with experiment result and characteristic of algorithm used for each reasoner.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.352-356
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• 2006

현존하는 추론 엔진들은 대부분 Tableaux 알고리즘 기반의 TBox의 최적화를 위한 연구를 진행하였다. 하지만 현실에서 대용량의 ABox를 추론하기 위한 유한한 시간 내에 결정 가능성을 보장하지 못한다. 따라서 실용성 있는 추론 엔진 효율을 위해서는 대용량 데이터를 가지는 ABox를 위한 최적화된 추론 기법이 필요하다. 본 논문에서는 OWL-DL 기반의 온톨로지(Ontology)를 데이터로그(Datalog)와 같은 규칙(Rule) 형태로 변형하여 관계형 데이터베이스와 같은 저장 시스템과 연동하기 위한 방법을 이용한다. 최종적으로 실세계의 환경에서의 데이터타입 속성(Datatype Property)이 포함된 SHIQ(D) 구성의 실용적인 추론 시스템을 수행하고자 한다. 따라서 OWL이 가지는 공리(Axiom)를 이용하여 데이터타입 속성이 포함된 규칙을 적용한 추론 방법에 대해서 제안하였다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.31-42
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• 2010

GPM(Generic Product Model) developed by Hitachi in Japan is a common data model to integrate and share life cycle data of nuclear power plants. GPM consists of GPM core model, an abstract model, implementation language for the model and reference library written in the language. GPM core model has a feature that it can construct a semantic network model consisting of relationships among objects. Initial GPM developed and provided GPML as an implementation language to support the feature of the core model, but afterwards the GPML was replaced by GPM-XML based on XML to achieve data interoperability with heterogeneous applications accessing a GPM data model. However, data models written in GPM-XML are insufficient to be used as a semantic network model for lack of studies which support GPM-XML and enable the models to be used as a semantic network model. This paper proposes OWL as the implementation language for GPM core model because OWL can describe ontologies similar to semantic network models and has an abundant supply of technical standards and supporting tools. Also, OWL which can be expressed in terms of RDF/XML based on XML guarantees data interoperability. This paper uses OWL DL, one of three sublanguages of OWL, because it can guarantee complete reasoning and the maximum expressiveness at the same time. The contents of this paper introduce the way how to overcome the difference between GPM and OWL DL, and, base on this way, describe how to convert the reference library written in GPML into ontologies based on OWL DL written in RDF/XML.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.285-292
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• 2013

The method of recent information retrieval passes into an semantic search to provide more accurate results than keyword-based search. But in common user case, they are still accustomed to using existing keyword-based search. Hence they are hard to create a typed structured query language. In this paper, we propose to ontology knowledge-base scheme for query interpretation of these user. The proposed scheme was designed based on the OWL-DL for description logic reasoning, it can provide a richer representation of the relationship between the object by using SWRL(Semantic Web Rule Language). Finally, we are describe the experimental results of the similarity measurement for verification of a user query semantic interpretation.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.123-139
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• 2011

Context-awareness as a key technology of ubiquitous computing needs a context model that understands and processes situational information coming from diverse sensors and devices, and can be applied diversely in various domains. Semantic web based ontologies use structured standard format and express meaning of information, so it is possible to recognize effectively context-awareness situations, allowing the system to share information and understand situation by inference. In this paper, we propose a layered ontology model to support generality and scaleability of the context-awareness system, and applied the model to u-Convention domain. In addition, we propose a effective reasoning method to handle compound situation by combining OWL-DL and SWRL rules.