• Korean Journal of Construction Engineering and Management
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• v.11 no.4
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• pp.12-21
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• 2010

Construction companies recently have been highly interested in developing information system as following the advanced of IT technology. Especially, with advent of knowledge-based paradigm, Knowledge Management System(KMS) has been actively built. However, current KMS is not optimized and not satisfied because KMS is not integrated with existing information system and has problems of method of knowledge management. The objectives of this research is to develop integrated KMS, which synthesizes knowledge and functions of scattered information system. This research investigates current KMS and analyzes the requirements of KMS. Based on the requirements, the utilization of construction portal is suggested. And integrated knowledge management method, which has connections with applications in construction portal, is suggested and the system is developed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.258-263
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• 2005

Haplotype-based analysis using high-density SNP markers have gained a great attention in evaluating genes in gene analysis and various clinical situations. However, there has been no research on disease diagnostic modeling based on SNPs analysis to our knowledge. The purpose of this study is to explore how knowledge discovery techniques are applied in medical informatics area and proposes a Case Based Reasoning (CBR) technique for diagnosis of gastric caner using Single Nucleotide Polymorphism(SNP).

• Journal of KIBIM
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• v.14 no.3
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• pp.22-30
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• 2024

Recently, LLM (Large Language Model), a rapidly developing generative AI technology, is receiving much attention in the smart construction field. This study proposes a methodology for implementing an knowledge expert system by linking BIM (Building Information Modeling), which supports data hub functions in the smart construction domain with LLM. In order to effectively utilize LLM in a BIM expert system, excessive model learning costs, BIM big data processing, and hallucination problems must be solved. This study proposes an LLM-based BIM expert system architecture that considers these problems. This study focuses on the RAG (Retrieval-Augmented Generation) document generation method and search algorithm for effective BIM data retrieval, with the goal of implementing an LLM-based BIM expert system within a small GPU resource. For performance comparison and analysis, a prototype of the designed system is developed, and implications to be considered when developing an LLM-based BIM expert system are derived.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.247-250
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• 2003

Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.1017-1030
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• 2021

Constructed upon Knowledge Management (KM) processes, the current study aims to investigate the interrelationship between Knowledge Sharing (KS) attitude among the faculty members and KM processes in higher education institutes (HEIs) in Pakistan along with the intervening role of subjective norms between KM processes and KS attitude. This research incorporated the theory of Planned Behavior (TPB) and the theory of Reasoned Action (TRA) to conceptualize the KS behavior by using a sample frame of 302 academic and administrative staff from research-based HEIs in Quetta, Pakistan. A questionnaire-based survey was conducted on permanent faculty members from different universities of Quetta, Pakistan. The finding of the study shows a positive attitude among the researchers. The study empirically examined the interface between KM processes and KS attitude and higher education performance while providing valuable insights into the prevailing literature by investigating the mediating role of subject norms. The impact of subjective norms on KS attitude and KM process indicates the importance and basic determinant in organizational premises and improvement of skills of faculty management in HEIs. The partial mediation also reveals the importance of subjective norms in the development of faculty members' KM and KS attitude process.

• The Journal of Information Systems
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• v.20 no.1
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• pp.1-20
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• 2011

This study investigated the factors that facilitate knowledge creation of team with the aspect of knowledge management. We considered two characteristics which are team members' psychological characteristics (achievement needs and conflict emotion) and knowledge network characteristics among team members (internal cohesion and external bridging) and verified the relationship between these characteristics and team performance. Furthermore, we examined whether these characteristics have a different effect on team performance according to the mastery climate. This study performed a survey targeting team members in knowledge based firms and 376 final surveys to be used as a sample in this study. The result showed that team members' psychological characteristics and knowledge network characteristics among Team members have an influence on team performance significantly. In addition, the master climate moderated the relationship between team members' psychological characteristics and team performance.

• The Journal of Information Systems
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• v.19 no.4
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• pp.65-85
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• 2010

The importance of communities of practice(CoP) as an organizational informal unit for fostering knowledge transfer and sharing gains a lot of attention from KM researchers and practitioners. Since most of CoPs are formulated online these days, the credibility or trustworthiness of knowledge contents circulated within a certain CoP should be considered thoroughly for them to be fully utilized safely. Here comes the need for an appropriate trust measuring methodology to determine the true value of knowledge given by unknown people through an online channel. In this paper, an improved trust measuring method is proposed using new trust variables such as level of degrees derived from the relationships among community users. In addition, activeness, relevance, and usefulness of the knowledge contents themselves, which are calculated automatically using a text categorization technique, are also used for trust measurement. The proposed framework incorporates fuzzy set and calculation concepts to help build trust matrices and models, which are used to measure the level of trust involved in specific knowledge artifacts concerned.

• Knowledge Management Research
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• v.9 no.4
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• pp.17-33
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• 2008

This study proposes University 2.0 as a model case of open, flexible, and distributed learning environment for higher education based on theoretical foundations and perspectives. As web 2.0 technologies emerge into the field of education, ways of generating and disseminating information and knowledge have been drastically changed. Professors are no longer the only source of knowledge. Students using internet often become prosumers of knowledge who search and access information through the web as well as publish their own knowledge using the web. A concept and framework of University 2.0 is introduced for implementing the new interactive learning paradigm with an open, flexible and distributed learning environment for higher education. University 2.0 incorporates online and offline learning environments with various educational media. Furthermore, it employs various learning strategies and integrates formal and informal learning through learning communities. Both instructors and students in University 2.0 environment are expected to be active knowledge generators as well as creative designers of their own learning and teaching.