• Proceedings of the Korean Society for the Gifted Conference
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• 2005.05a
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• pp.173-180
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• 2005

The purpose of this study was to identify common and domain-specific cognitive characteristics of gifted students based on a hierarchical structural model of human abilities. This study is based on the premise that abilities identified by tests can appear as observable characteristics in test or school situations. Abilities proposed by major models of intelligence were reviewed in terms of their power to explain cognitive characteristics of gifted students. However, due to the lack of their explanatory power and disagreement on common and domain-specific cognitive abilities, a new hierarchical structural model was conceptualized in a unique way based on interrelationships between abilities proposed by the models. The newly established model hypothesizes a cognitive mechanism that accounts for how domain-specific knowledge is formed, as well as which abilities are common and domain-specific, how they are related functionally, and how they account for common and domain-specific cognitive characteristics of gifted students. The cognitive mechanism has important implications for our understanding of the chronically controversial concepts, 'intelligence' and 'knowledge.' Clearer definitions of what intelligence is (g or multiple), what knowledge is, and how knowledge develops ('genetic or environmental,' 'rationalistic or empiricist') may result from this model.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.3 s.180
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• pp.22-31
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• 2006

This paper introduces an approach to an ontology-based knowledge framework for product life cycle management (PLM). Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects. Therefore, we suggest an ontology-based knowledge framework including knowledge maps, axioms and specific knowledge far domain. The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so that ambiguity of the semantics can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain common knowledge and guides engineers to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and product item level for PLM. The top level is specialized knowledge fer a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of unambiguous knowledge for PLM and is represented with first-order logic to maintain a uniform representation.

• 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.

• 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.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.99-109
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• 2005

This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.

• 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.

• 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 Information Processing Systems
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• v.17 no.5
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• pp.867-878
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• 2021

In context awareness and user intention tasks, dataset construction is expensive because specific domain data are required. Although pretraining with a large corpus can effectively resolve the issue of lack of data, it ignores domain knowledge. Herein, we concentrate on data domain knowledge while addressing data scarcity and accordingly propose a multi-channel long short-term memory (LSTM). Because multi-channel LSTM integrates pretrained vectors such as task and general knowledge, it effectively prevents catastrophic forgetting between vectors of task and general knowledge to represent the context as a set of features. To evaluate the proposed model with reference to the baseline model, which is a single-channel LSTM, we performed two tasks: voice phishing with context awareness and movie review sentiment classification. The results verified that multi-channel LSTM outperforms single-channel LSTM in both tasks. We further experimented on different multi-channel LSTMs depending on the domain and data size of general knowledge in the model and confirmed that the effect of multi-channel LSTM integrating the two types of knowledge from downstream task data and raw data to overcome the lack of data.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.651-654
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• 2005

Ontology developing process has aroused a lot of controversy among knowledge engineers and knowledge users. The recent surges on ontology building methodologies and practical ontology applications have explored a broad spectrum of knowledge management challenges. On the one hand, the abundant methodology theories provide us with a set of useful heuristic rules, from which we get the overview of ontology building process. But on the other hand, every research groups would like to justify their theories by listing their specific characteristics and unique method when approaching the right way. However, there is still no one “correct” way or methodology for developing ontologies. In this case, the methods used to evaluate only a subset of specific domain do not make any sense to the commonsense users. As a result, a comprehensive understanding of domain ontology is urgent and necessary.

• Journal of Science Education
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• v.40 no.1
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• pp.1-16
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• 2016

The purpose of this study is to explore the variables of knowledge, acceptance of theory of evolution and epistemology that could be keys for teaching and learning the theory of evolution within school contexts, and to suggest instructional tips for teaching evolution in relation to the grade levels of education. This cross-sectional study examined the grade level differences (8th, 11th, and preservice teachers) of four variables: evolutionary knowledge; acceptance of theory of evolution; and both domain-specific epistemology (nature of science in relation to evolution) and context-specific epistemology (scientific epistemological views) and their relationships. This study, then, built conceptual models of each grade level students' acceptance of theory of evolution among the factors of evolutionary knowledge and epistemology (both domain-specific and context-specific). The results showed that the scores of evolutionary knowledge, evolution in relation to NOS, and scientific epistemology increased as the grade levels of education go up(p<.05) except the scores of acceptance of theory of evolution(p>.05). In addition, the 8th graders' and the 11th graders' acceptance of evolutionary theory was most explained by 'evolution in relation to NOS', while the preservice teachers' acceptance of evolutionary theory was most explained by evolutionary knowledge. Interestingly, 'scientific epistemological views' were only included for the 8th graders, while evolutionary knowledge and 'evolution in relation to NOS' (context-specific epistemology) were included in explaining all the level of students' acceptance of evolutionary theory. This study implicated that when teaching and learning of the theory of evolution in school contexts, knowledge, acceptance of evolutionary theory and epistemology could be considered appropriately for the different grade levels of students.