• Korean Journal of Cognitive Science
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• v.11 no.3_4
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• pp.73-81
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• 2000

This study was conducted to investigate some characteristics of representation of category knowledge and script knowledge. Using primed lexical decision task with higher level primers in the representation structure, Experiment 1 examined the interaction effects between knowledge type and concept typicality. It was found that the concept typicality has some effects in category representation, while it has no significant effect in script representation. In Experiment 2, primers of the lower hierarchy in the representation structure were employed. The results showed that the main effect of knowledge type was significant: the response time for category knowledge was faster than that for script knowledge. Typicality effect did not show in this experiment. The results of t the two experiments suggest that category knowledge is represented in hierarchy and typicality. while script knowledge may lack in that characteristics. Other aspects of the differences in characteristics of category- and script- knowledge representation were discussed,

• Journal of Educational Research in Mathematics
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• v.8 no.2
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• pp.553-563
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• 1998

In this thesis, I examined Bruner's EIS theory from the viewpoint of epistemology based on Piaget's genetic epistemology. Although Bruner's ideal thought which insisted ‘to teach the structure’accepted Piaget's theory in the methodology of realization, it is different from Piaget in understanding knowledge. The difference is shown from understanding the meaning of ‘structure’. Piaget's concept of structure is something that has overcome the realistic viewpoint of the traditional epistemology and is reconstructed through endless self-regulative transformational process. However Bruner's is used as a realistic meaning as we can see in the Plato's recollection theory. Therefore Piaget's ‘stage of development’means the difference of structure which lies in the generative process and it includes the qualitive difference of level. On the other hand, Bruner, who is trying to translate and suggest the fixed structure to the children understood Piaget's stage of development as the difference in the ways of representation. Piaget's operational constructivism insists that the children should ‘construct’the knowledge through their activity, and especially in case of the lohico-mathematical recognition, the source should be internalized activity, that is, operation. In view of this assertion, Burner's idea which insists to accept the structure of knowledge as a fixed reality and to suggest the translated representation proper to the cognitive structure of the children to teach them, has a danger of emphasizing only the functional aspects to deliver the given knowledge ‘quickly’. And it also has the danger of damaging ‘the nature of the knowledge’in the translated knowledge.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.798-803
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• 2005

The increasing complexity of modem products requires the effective management of design knowledge, which partly resides in the product itself on the one hand. On the other hand, a lot of knowledge is gathered and/or generated during the design process, but disappears as the design project concludes. This paper describes a knowledge representation method to accommodate the implicit design knowledge. The method is based on the FBS(Function-Behavior-Structure) model and extends the object ontology with constraint entity. An example to represent the injection mold design knowledge is given to show its applicability.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.383-390
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• 2012

In this paper, we suggest an information retrieval visualization tool using the knowledge representation method. Information retrieval visualization tool suggested in this paper is designed to automatically extract retrieval intention using user's search history data and visualize extracted retrieval intention in the knowledge representation method structure. A psychological knowledge representation methodology was adopted for schema for retrieval intention representation and its effectiveness has been proved through the behavioral experiments. Result of experiment revealed that information retrieval visualization tool has been improved approximately 39% in user satisfaction compared to existing retrieval method, suggesting a measure to solve re-retrieval problem in the process of information retrieval.

• Journal of the Korea Society for Simulation
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• v.4 no.1
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• pp.1-11
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• 1995

The model of a FMS (Flexible Manufacturing System) admits to a natural hierarchical decomposition of highly decoupled units with similar structure and control. The FMS fractal architecture model represents a hierarchical structure built from elements of a single basic design. A SES (System Entity Structure) is a structural knowledge representation scheme that contains knowledge of decomposition, taxonomy, and coupling relationships of a system necessary to direct model synthesis. A substructure of a SES is extracted for use as the skeleton for a model. This substructure is called pruned SES and the extraction operation of a pruned SES from a SES is called pruning (or pruning operation). This paper presents a pruning operation called recursive pruning. It is applied to SES for generating a model structure whose sub-structure contains copies if itself as in FMS fractal architecture. Another pruning operation called delay pruning is also presented. Combined with recursive pruning the delay pruningis a useful tool for representing and constructing complex systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1-4
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• 2003

Knowledge classification and expression of constructed knowledge have been main research issues in the field of knowledge representation. Constructed design knowledge of the former product loses its utility when new products with different structures are introduced to the market. In order to construct the design knowledge for a new product. designers need to reconstruct the design knowledge with new relationships. The design knowledge has been constructed with level trees, but it is difficult to rearrange the relations. Design DNA is proposed in this work in order to facilitate the rearrangement of design knowledge and give flexibility to knowledge structure. Design DNA is based on Layout-oriented domain knowledge and Function-oriented domain knowledge, which enables to generate new design knowledge that will result in new part geometries for given constraints on the part functions. Design DNA is applied to the design knowledge of lever system of the automatic transmission of passenger cars as an example.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.71-83
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• 1999

Conventional symbolic inference systems lack flexibility because they do not well reflect flexible semantic structure of knowledge and use symbolic logic for their basic inference mechanism. For solving this problem. we have recently proposed the 'Connectionist Semantic Network(CSN)' as a model for flexible knowledge representation and inference based on neural networks. The CSN is capable of carrying out both approximate reasoning and commonsense reasoning based on similarity and association. However. we have difficulties in representing general and structured high-level knowledge and variable binding using the connectionist framework of the CSN. In this paper. we propose a hybrid system called SymCSN(Symbolic CSN) that combines a symbolic module for representing general and structured high-level knowledge and a connectionist module for representing and learning low-level semantic structure Simulation results show that the SymCSN is a plausible model for human-like flexible knowledge representation and inference.

• Trans-
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• v.14
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• pp.65-92
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• 2023

The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.184-204
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• 2015

Fuzzy Formal Concept Analysis (FCA) is a mathematical tool for the effective representation of imprecise and vague knowledge. However, with a large number of formal concepts from a fuzzy context, the task of knowledge representation becomes complex. Hence, knowledge reduction is an important issue in FCA with a fuzzy setting. The purpose of this current study is to address this issue by proposing a method that computes the corresponding crisp order for the fuzzy relation in a given fuzzy formal context. The obtained formal context using the proposed method provides a fewer number of concepts when compared to original fuzzy context. The resultant lattice structure is a reduced form of its corresponding fuzzy concept lattice and preserves the specialized and generalized concepts, as well as stability. This study also shows a step-by-step demonstration of the proposed method and its application.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1171-1174
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• 1993

A promising approach to get the benefits of neural networks and fuzzy logic is to combine them into an integrated system to merge the computational power of neural networks and the representation and reasoning properties of fuzzy logic. In this context, this paper presents a fuzzy neural network which is able to code fuzzy knowledge in the form of it-then rules in its structure. The network also provides an efficient structure not only to code knowledge, but also to support fuzzy reasoning and information processing. A learning scheme is also derived for a class of membership functions.