• 정보관리학회지
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• 제15권3호
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• pp.133-150
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• 1998

본 연구에서는‘조직지식중심적 지식경영’을 위해 지식창조원리로서 음양이론을 도입하여 영역지식 (陽의 지식)과 업무지식(陰의 지식)이 음양(陰陽)의 순환적 구조로서 상호 작용하여 조직지식으로 창출되는 과정을 저장하여 재활용하기 위한 지식 창조적 조직메모리를 제안하였다. 지식 창조적 조직메모리 구축을 위하여 객체 지향적 방법론을 적용하여 영역지식과 업무지식의 순환적 흐름을 주도하는 3개 지식 컴퍼넌트를 설정하여 조직지식을 설계하였다. 조직지식은 기존의 정보시스템에 포함된 데이터베이스 스키마. 프로세스 모델 또는 지식베이스의 의미네트워크(Semantic Network), 프레임(Frame) 등을 수용하기 위해 (i) 지식객체와 (ⅱ) 객체간의 관계 및 (ⅲ) 관계정도를 정의한 그래프구조로서 설계하였다. 이러한 조직지식의 설계는 지식마이닝 기법인 사례기반추론(Case Based Reasoning)등을 활용한 새로운 조직지식의 생성에 기여할 수 있다.

• 한국지능시스템학회논문지
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• 제15권5호
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• pp.632-638
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• 2005

This paper describes a new data-handing, based on a Spatial Human Interface as human indicator, to the Spatial-Knowledge-Tags (SKT) in the spatial memory the Spatial Human Interface (SHI) is a new system that enables us to facilitate human activity in a working environment. The SHI stores human activity data as knowledge and activity history of human into the Spatial Memory in a working environment as three-dimensional space where one acts, and loads them with the Spatial-Knowledge-Tags(SKT) by supporting the enhancement of human activity. To realize this, the purpose of SHI is to construct new relationship among human and distributed networks computers and sensors that is based on intuitive and simultaneous interactions. In this paper, the specified functions of SKT and the realization method of SKT are explained. The utility of SKT is demonstrated in designing a robot motion control.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2006년도 춘계학술발표대회
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• pp.1471-1480
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• 2006

• 경영정보학연구
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• 제18권4호
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• pp.155-171
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• 2016

오늘날 조직은 팀으로 구성되어 있고 팀들의 지식관리를 지원하는 정보기술에 많은 투자를 하고 있으며, 팀 성과를 높이기 위한 교류기억시스템의 활용에 관한 중요성도 증가하고 있다. 본 연구의 목적은 지식관리를 지원하는 정보기술과 교류기억시스템이 팀 성과에 미치는 영향에 있어서 지식(형식지, 암묵지)의 공유 및 활용의 매개효과를 살펴보는 것이다. 이를 위해 지식관리를 지원하는 정보기술을 사용하고 있는 다양한 업종의 근로자 37개 팀 224명 응답자의 자료를 사용하여 구조방정식으로 분석하였다. 그 결과는 다음과 같다. 첫째, 지식관리를 지원하는 정보기술은 교류기억시스템에 높은 영향을 미치는 것으로 밝혀졌다. 둘째, 지식관리를 지원하는 정보기술은 직접 지식(형식지, 암묵지) 공유 및 활용에 미치는 효과보다 교류기억시스템을 매개로 하는 것이 더 높은 효과가 있었다. 그리고 지식관리를 지원하는 정보기술은 지식 활용보다 공유에 더 높은 효과가 있었다. 셋째, 교류기억시스템은 암묵지 공유, 형식지 공유, 암묵지 활용, 형식지 활용 순으로 유의미하게 나타났다. 마지막으로 지식(형식지, 암묵지) 공유 및 활용과 팀 성과와의 관계에서 암묵지 활용, 암묵지 공유, 형식지 활용 순으로 유의미하게 나타났다.

• ETRI Journal
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• 제44권3호
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• pp.438-449
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• 2022

This study proposes a dependency grammar-based self-attention multilayered bidirectional long short-term memory (DG-M-Bi-LSTM) model for subject-predicate-object (SPO) tuple recognition from natural language (NL) sentences. To add recent knowledge to the knowledge base autonomously, it is essential to extract knowledge from numerous NL data. Therefore, this study proposes a high-accuracy SPO tuple recognition model that requires a small amount of learning data to extract knowledge from NL sentences. The accuracy of SPO tuple recognition using DG-M-Bi-LSTM is compared with that using NL-based self-attention multilayered bidirectional LSTM, DG-based bidirectional encoder representations from transformers (BERT), and NL-based BERT to evaluate its effectiveness. The DG-M-Bi-LSTM model achieves the best results in terms of recognition accuracy for extracting SPO tuples from NL sentences even if it has fewer deep neural network (DNN) parameters than BERT. In particular, its accuracy is better than that of BERT when the learning data are limited. Additionally, its pretrained DNN parameters can be applied to other domains because it learns the structural relations in NL sentences.

• Journal of Information Processing Systems
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• 제17권5호
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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.

• 대한지구과학교육학회지
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• 제3권1호
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• pp.18-27
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• 2010

The purpose of this study is to investigate effects of instruction with stories on elementary school students' science learning and memory. For the purpose, this researcher sampled 3 classes in their 3th grade from an elementary school. Out of the three classes, two were designated as the comparative group consisting of 70 students and the other, the experimental group, 32 students. The former group was applied instruction treatment under the 7th national curriculum of education. The other group was instructed with a story book that contained stories students already knew which were somewhat rearranged to comply with contents of a relevant curricular course. Results of the study can be described as follows. First, academic achievement test was made immediately after the treatment to show that the experimental group was significantly higher in scores for memory and understanding in the section of 'Finding Constellations' that the other group. Second, the two groups' academic achievements in relation to the section, 'Finding Constellations' were tested 3 months after the treatment to show that the experimental group was significantly higher in scores for memory and understanding than the comparative group. Such achievements within the groups were tested 3 months after the treatment to find that both of the two groups didn't show statistically significant differences.

• 전자공학회논문지
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• 제50권4호
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• pp.83-88
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• 2013

최근 들어 뇌과학적인 연구가 활발해짐에 따라 두뇌기능을 공학적으로 응용하려는 연구가 많아지고 있다. 두뇌 기능 중 기억과 감정을 담당하는 부분을 살펴보면 기억을 담당하는 해마체와 감정중추인 편도체가 긴밀히 협조하고 있는 것을 알 수 있다. 실제적으로 지식은 감정에 영향을 미치고 감정은 지식에 영향을 미친다. 인간의 모든 판단과 결정에 있어서 감정요소는 배제할 수 없는 아주 중요한 영향을 미친다. 보다 정교한 지능 시스템을 구축하려면 감정이 결합된 지식베이스를 설계하여야 한다. 따라서 본 논문에서는 해마체와 편도체의 공조 시스템에 착안하여 지식과 감정이 결합된 지식감정 결합 시스템을 설계하고 기억회상과 추론 과정에서 변화하는 감정 상태의 추이를 감지하는 메커니즘을 제안하고자 한다.

• 가정과삶의질연구
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• 제26권4호
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• pp.41-54
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• 2008

The purpose of this study was to investigate predictors concerning preschoolers' ability to read words, in terms of their sub-skills of alphabet knowledge, phonological awareness, and phonological processing. Fourteen literacy sub-tests and three types of reading tasks were administered to 289 kindergartners aged 4 to 6 in Busan. The main results are as follows. Sub-skills that predicted reading ability varied with children's age. Irrespective of children's age groups, knowledge of consonant names and digit naming speed commonly explained the reading of real words. In contrast, skills of syllable deletion and phoneme substitution and knowledge of alphabet composition principles were related to only 4-year-olds' reading skills. Exclusively included was digit memory in predicting 5-year-olds' reading abilities, and knowledge of vowel sounds in 6-year-olds' reading skills. The type of reading task also influenced reading ability. A few common variables such as knowledge of consonant names and vowel sounds, digit naming speed, and phoneme substitution skill explained all types of word reading. Syllable counting skills, however, had predictive value only for the reading of real words. Phoneme insertion skills and digit memory had predictive value for the reading of pseudo words and low frequency letters. Likewise, knowledge of consonant sounds and vowel stroke-adding principles were significant only for the reading of low frequency letters.

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.527-535
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• 2003

A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memory and Long Term Memory. In particular, to solve delayed-reward problem, a knowledge-propagation (KP) method is proposed, where well-designed or well-trained S-R(stimulus-response) associations for low-level sensors are utilized to learn new S-R associations for high-level sensors, in case that those S-R associations require the same objective such as obstacle avoidance. To show the validity of our proposed KP method, comparative experiments are performed for the cases that (ⅰ) only a delayed reward is used, (ⅱ) some of S-R pairs are preprogrammed, (ⅲ) immediate reward is possible, and (ⅳ) the proposed KP method is applied.