• Journal of Korean Elementary Science Education
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• v.25 no.3
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• pp.257-270
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• 2006

The purpose of this study was to develop elementary students' ability to generate hypothesis knowledge through knowledge generation learning in science. The learning program consisted of a series of 28 activities to generate hypotheses in science. Eighty 6th grade students participated in the study and were divided into experimental and control groups. The experimental group was administered a program geared towards hypothesis generation learning and the control group was administered a program aimed at hypothesis expository learning in elementary science. After using the respective programs, subjects in both groups were tested in terms of their abilities in abductive knowledge generation and administered a descriptive self-report regarding their generation of hypotheses. Two of the 28 activity program worksheets in the experimental group were analyzed in terms of the quality and process of students' hypothesis generation. The results were as follows: 1) The experimental group showed significantly higher scores in terms of scientific knowledge generation (i.e. abductive knowledge generation) than the control group. 2) The degree of hypothesis explanation in the experimental group was significantly higher than in the control group in terms of the quality of the generated hypotheses. In addition, students in the experimental group generated more varied and valid knowledge than the control group in terms of sub-knowledge of hypothesis generation. Therefore, it can be argued that this program for hypothesis knowledge generation in elementary science students was effective in the generation of hypothesis knowledge.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.7
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• pp.720-728
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• 1990

A learning control method is proposed in this paper, using a knowledge base which contains control rules, data, and patterns of the past experience of a plant. The knowledge for plant control is retrieved from measurement data during operation and continually modified after control performance evaluation. A control method is proposed using tinually modified after control performance evaluation. A control method is proposed using fuzzy model of the plant and a recursive statistic decision method of fuzzy subset for control rule generation. Also, the resulting knowledge-based control algorithm has been applied to aprocess and its performance improvement and proper generation of appropriate control rules have been verified.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.63-69
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• 2015

There are various researches which proposed an automatic instance generation from freetext on the web. Existing researches that focused on English, adopts pattern representation which is generated by simple rules and regular expression. These simple patterns achieves high performance, but it is not suitable in Korean due to differences of characteristics between Korean and English. Thus, this paper proposes a novel method for generating patterns and instances which focuses on Korean. A proposed method generates high quality patterns by taking advantages of dependency relations in a target sentences. In addition, a proposed method overcome restrictions from high degree of freedom of word order in Korean by utilizing postposition and it identifies a subject and an object more reliably. In experiment results, a proposed method shows higher precision than baseline and it is implies that proposed approache is suitable for self-knowledge learning system.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.5-18
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• 2014

This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

• Journal of Information Technology Applications and Management
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• v.15 no.3
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• pp.261-273
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• 2008

The starting point of knowledge generation and management is the enhancement of learning capability and capacity of organizational members. Organizational change for learning environment should be aligned with the change of organizational strategy, structure and processes. The study employed action learning methodology to constitute learning organization processes. The treatment effect to institute learning organization has been successful thanks to the members' zeal and consensus to change the processes. However, not every learning team has been so successful. Some cases complained time consuming where others expect to be helpful for their incentives. The researchers concluded that the most important point for success of the learning organization project should be the support of top management.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.27-38
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• 2023

In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.

• Knowledge Management Research
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• v.9 no.1
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• pp.147-161
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• 2008

In the previous KM (Knowledge Management) studies, it has been repeatedly pointed that CoP (Community of Practice) should be used as a platform for boosting up corporate innovative activities. Despite this, it is very rare to find relevant literature in which real-world cases are introduced showing critical success factors, implemented strategies, and objective analysis of results. In this sense, main objective of this paper is very timely- to introduce a real-world CoP case in which POSCO, world-leading steel company, sorted out creative CoP strategies to nurture knowledge-sharing activities to solve various kinds of problems at hand, and maintain appropriate level of knowledge circulation throughout all the working units of company. In a nutshell, POSCO has been successful in any measure in utilizing the creative CoP activities as strategic means to change the paradigm of innovation and extract fruitful outcomes from integrating three important individual activities such as work, learning, and innovation.

• Journal of Korean Elementary Science Education
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• v.33 no.3
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• pp.566-578
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• 2014

The purpose of this study is to develop a program for elementary school students' scientific experimental design knowledge generation. This study also investigated the effects of their experimental design ability, as well as the change in the type and elaborateness of their experimental design by applying the program. The subjects of this study was 4 classes in 6th grade of an elementary school located in Seoul, KOREA. The classes were divided into experimental and comparative groups. While the treatment was applied to the experimental group, the comparative group was taught using conventional methods. The pre-test and post-test for students' capability of building scientific experimental design knowledge were conducted to compare the ability of experimental design, the change in the type and elaborateness of experimental design. The findings in this study are as follows: First, the program appeared to be effective in improving experimental design ability. Furthermore, the program appeared to be more effective in generating a higher level of the experimental design type and elaborateness. Therefore, in order to improve experimental design knowledge generation ability, the program can be utilized as effective learning model in elementary school.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.351-368
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• 2005

The manual construction of the knowledge-base takes much time and effort, and it is hard to adjust intelligence systems to dynamic and flexible environment. Thus mental development in those systems has been investigated in recent years. Autonomous mental development is a new paradigm for developing autonomous machines, which are adaptive and flexible to the environment. Learning conversation, a kind of mental development, is an important aspect of conversational agents. In this paper, we propose a learning conversation method for conversational agents which uses several promising techniques; speech-act templates and genetic programming. Knowledge acquisition of conversational agents is implemented by finite state machines and templates, and dynamic sentence generation is implemented by genetic programming Several illustrations and usability tests how the usefulness of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.