• Korean Journal of Child Studies
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• v.29 no.5
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• pp.243-269
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• 2008

The role of domain-specific causal mechanism information and domain-general conditional probability in young children's causal reasoning on physics and psychology was investigated with the participation of 121 3-year-olds and 121 4-year-olds recruited from seven child care centers in Seoul, Kyonggi Province, and Busan. Children watched moving pictures on physical and psychological phenomena, and were asked to choose an appropriate cause and justify their choice. Results showed that young children's causal reasoning differed depending on domain-specific mechanism. In addition, their causal reasoning on physics and psychology differed by the developmental level of causal mechanism. The interaction of domain-specific mechanism and domain-general conditional probability influenced children's causal reasoning : evident conditional probability between domain-appropriate cause and effect helped children make more inferences based on domain-specific causal mechanism.

• Journal of Families and Better Life
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• v.26 no.5
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• pp.333-354
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• 2008

This study aimed to investigate the role of domain-specific causal mechanism information and domain-general conditional probability in young children's causal reasoning on psychology and biology. Participants were 121 3-year-olds and 121 4-year-olds recruited from seven childcare centers in Seoul, Kyonggi Province, and Busan. After participants watched moving pictures on psychological and biological phenomena, they were asked to choose appropriate cause and justify their choices. Results of this study were as follows: First, young children made different inferences according to domain-specific causal mechanisms. Second, the developmental level of causal mechanisms has a gap between psychology and biology, and biological knowledge was proved to be separate from psychological knowledge during the preschool period. Third, young children's causal reasoning was different depending on the interaction effect of domain-specific mechanisms and domain-general conditional probability: children could make more inferences based on domain-specific causal mechanisms if conditional probability between domain-appropriate cause and effect was evident. To conclude, it can be inferred that the role of domain-specific causal mechanisms and domain-general conditional probability is not competitive but complementary in young children's causal reasoning.

• The Journal of Information Systems
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• v.17 no.4
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• pp.341-367
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• 2008

This study propose a model relating supplier's use of IOIS(Inter-Organizational Information Systems) to strategic benefits through extension of Subramani's research model. In extended model, collaboration serves as a safeguard for relationship-specific intangible asset. Specifically, we evaluate how two patterns of IOIS use by supplier(exploitation and exploration) relate to two specific types of relationship-specific intangible asset(business process specificity and domain knowledge specificity), which in turn are posited to promote collaboration and strategic benefits. To explore the current study, questionnaire survey was conducted on 72 first-tier supplier firms in the manufacturing industry. Based on the survey results, we posits the following : (1) Each pattern of IOIS use directly promotes a specific type of relationship-specific intangible asset. The path of the relationship between IOIS use for exploitation and domain knowledge specificity is positive but not significant. The other paths are positive and significant. (2) Both types of relationship-specific intangible asset have a positive and significant impact on collaboration. (3) Domain knowledge specificity influences on strategic benefits but business process specificity does not have an effect on them. (4) Collaboration affects supplier's strategic benefits. These findings provide a deeper understanding of the mechanism of how the pattern of IOIS use can result in strategic benefits for supplier firms.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.353-360
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• 2004

Ontology defines the terms used in a specific domain and the relationships between them and represents them as hierarchical taxonomy. The present paper proposes a semi-automatic domain-specific ontology construction method based on terminology Processing. For this purpose, it presents an algorithm to extract terminology according to the noun/suffix pattern of terminology in domain texts and find their hierarchical structure. The experiment was carried out using pharmacy-related documents. As singleton terminology with noun/suffix were identified, the average accuracy was 92.57%. In case of multi-word terminology, the average accuracy was 66.64%. The constructed ontology forms natural semantic clusters with based on suffices and semantic information, so can be utilized in approaches to specific knowledge such as information look-up or as the base of inference to improve searching abilities.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.2
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• pp.145-166
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• 2019

While a significant number of user-related models have been presented in Human Information Behavior (HIB) research community, the basic assumption of the present study is most of those models including information interaction models are multi-domain models associated with comprehensive research components. Based on such an assumption, this study discusses the shortcomings of multi-domain models and proposes the need to present a new type of model. Accordingly, the study elaborates four essential models of HIB reach community and presents a new type of model based on Specific Domain Focus Modeling (SDFM). As an example of such modeling, this study presents the present author's information retrieval interaction model based on the degree of connections between systems and information resources.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.525-534
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• 2006

Ontology specifies the knowledge in a specific domain and defines the concepts of knowledge and the relationships between concepts. It is possible to provide the service based on the semantic web through the ontology. Therefore, to specify and define the knowledge in a specific domain, it is required to generate the ontology which conceptualizes the knowledge. Accordingly, to search the information of potential customers for home-delivery marketing of post office, we design the specific domain to generate the ontology based on the semantic web in this paper. And we propose how to retrieve the information, using the generated ontology. We implement the data search robot which collects the information based on the generated ontology. Also, we confirm that the ontology and the search robot perform the information retrieval exactly.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.41-53
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• 1993

The tasks which detect and track moving objects, by analyzing dynamic images taken at a constant time interval, are essential in various applications. This paper suggests how to utilize domain-specific knowledge and motional knowledge for detecting and tracking moving objects. That is, The trajectory information of a moving object is to be used for generating hypotheses on expected motion and expected position of moving objects, and the domain-specific knowledge is to be used for verifying the generated hypotheses.

• Annual Conference of KIPS
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• 2004.11a
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• pp.591-594
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• 2004

Existing methodologies and practical ontology development experiences have explored a broad spectrum of knowledge management challenges. Each has its own characteristics and evaluates only a subset of specific domain. However, there is still no one 'correct' way or methodology for developing ontologies. In this paper, we described a methodology for domain driven ontology development, covering the whole lifecycle from the formalization of domain to the evolution of ontologies.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.212-220
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• 2023

Ontologies are knowledge containers in which information about a specified domain can be shared and reused. An event happens within a specific time and place and in which some actors engage and show specific action features. The fact is that several ontology models are based on events called Event-Based Models, where the event is an individual entity or concept connected with other entities to describe the underlying ontology because the event can be composed of spatiotemporal extents. However, current event-based ontologies are inadequate to bridge the gap between spatiotemporal extents and participants to describe a specific domain event. This paper reviews, describes, and compares the existing event-based ontologies. The paper compares and contrasts various ways of representing the events and how they have been modelled, constructed, and integrated with the ontologies. The primary criterion for comparison is based on the events' ability to represent spatial and temporal extent and the participants in the event.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1752-1761
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• 2007

Location-based services are a recent concept that integrates a mobile device's location with other information in order to provide added value to a user. Although Location-based Services provide users with comfortable information, it is a complex task to manage and share heterogeneous and numerous data in decentralized environments. In this paper, we propose the Semantic LBS Model as one of the solution to resolve the problem. The Semantic LBS Model is a LBS middleware model that includes an ontology-based data model for LBS POI information and its processing mechanism based on Semantic Web technologies. Our model enables POI information to be described and retrieved over various domain-specific ontologies based on our proposed POIDL ontology. This mechanism provide rich expressiveness, interoperability, flexibility in describing and using information about POls, and it can enhance POI retrieval services.