• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.109-118
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• 2012

This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.

• International Commerce and Information Review
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• v.12 no.2
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• pp.325-355
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• 2010

Knowledge-based exporting companies in Korea have reached a stage to develop new technological innovation and to pioneer new markets. But, developing new technologies and launching new products require an enormous sum of money for Research and Development(R&D) and there is still uncertainty in technological development and markets. Therefore, through open technological innovation, they are encouraged to actively use external technological sources and ideas. They also need to enhance the efficiency of the relatively little R&D investment. In this paper, firstly, it conducts a precedent study on the concept and influence factors of knowledge-based exporting companies and open technological innovation. Secondly, it sets a study model and estimates a regression coefficient to analyze the influence factors of open technological innovation of knowledge-based exporting companies which are using external resources on the process of innovation. Through case study and empirical analysis, we are going to find the implication of open technological innovation and prepare the way of the innovation for the knowledge-based exporting companies. According to the empirical analysis, variables such as firm size, processing degree, product life, patent registration, maintaining internal security didn't have positive effects on open innovation performance. On the other hand, research capability and market preoccupancy had positive effects. Therefore, to succeed in open innovation, knowledge-based exporting companies not only need to secure research capability through open innovation, but also need to preoccupy the market through commercialization of developed product.

• Agribusiness and Information Management
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• v.8 no.1
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• pp.11-16
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• 2016

This paper presents how Digital Knowledge Ecosystem such as "Govi Nena" (translates as agriculture intelligence) can be used to provide a more effective and practical solution to eliminate the inefficiencies in agricultural markets and achieve higher productivity and price stability. In order to establish the framework to analyze the system, this paper uses a set of hypothetical scenarios faced by value chain actors based on a review of the literature, established knowledge and recent developing country experiences. The scenario analysis reveals that "Govi Nena" enables farmers to make effective production decisions, deepens the level of value chain integration, and enhances the level of welfare for the society as a whole.

• Korean Management Science Review
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• v.11 no.2
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• pp.65-77
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• 1994

One of the major issues in the implementation and maintenance of CIM databases is the sharing and exchange of information among the heterogeneous databases. This paper addresses some architectural aspects for integrating the heterogeneous multi-databases using knowledge-based expert systems. we propose a loosely integrated coupling system between databases and knowledge-based expert systems. Especially we suggest the architectural aspects of such a coupling methodology. we also present the structure and knowledge representation scheme for the proposed knowledge-based expert system. A prototype example is included to illustrate the framework and its mechanism for implementation.

• Journal of the Korean Society for Library and Information Science
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• v.36 no.3
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• pp.115-132
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• 2002

This study is an examination of knowledge-based society's impact on knowledge, it's functions, and it's types in fields of humanities an social sciences. Knowledge-based society does not invalidate the definitive mechanism underpinning social coexistence today, but the importance of knowledge will increase greatly whereas the importance of the productive resources labor and capital will diminish. Therefore, knowledge-based society demands that we enter at this time into a discussion that takes new approaches to the knowledge. This study provides a doorway to a discussion of topics such as : Anticipating and characterizing the knowledge-based society, spectrum of fields of new types of knowledge for which typical differences can be ascertained, the interlinking of various disciplines in the respective field of knowledge, the new roles and types of knowledge in the fields of humanities and social sciences.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.57-75
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• 2004

The knowledge management is increasingly an important strategic weapon for sustaining competitive advantage of firms. Firms are undertaking knowledge management initiatives and making significant investments. However, there is relatively little empirical support for the impact of knowledge management on performance of firms. Understanding of the impact of knowledge management, this paper explores how knowledge management strategy influences firms' market value. We examine this issue using event study methodology and evaluate the cumulative abnormal returns for knowledge management strategy announced by firms from 1998 to 2002. The results show that firms' announcements of knowledge management strategy are positively related with firms' market value. Specially, dynamic style-which emphasizes both (i) knowledge reusability through information technologies and (ii) knowledge sharing through informal discussions among employees-has higher performance. This outcome presents empirical support to argument that the emphasis on both tacit and explicit knowledge results in better market value.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.41-67
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• 1999

ERP is now one of the prevailing applications for integrated information systems, So far, the conventional ERPs lack how to manage knowledge of making decisions, that is one of the important goal of ERP. This gives a motivation on adding decision support capabilities to the ERPs: active advice for business analysis, evaluation and control. In this paper, we proposed an agent-based intelligent ERP that is operated on the Internet. In special, knowledge of economic value added (EVA) is explicitly acquired as a set of data, models and methodologies, A new knowledge representation format, MIF, is suggested to show the communication mechanism between agents, The agent-based knowledge processing is adopted to deliver intelligence on the Internet.

• Journal of KIBIM
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• v.12 no.4
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• pp.52-60
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• 2022

Recently, the demand for connection between various heterogeneous dataset and BIM as a construction data model hub is increasing. In the past, in order to connect model between BIM and heterogeneous dataset, related dataset was stored in the RDBMS, and the service was provided by programming a method to link with the BIM object. This approach causes problems such as the need to modify the database schema and business logic, and the migration of existing data when requirements change. This problem adversely affects the scalability, reusability, and maintainability of model information. This study proposes an ontology BIM-based knowledge service framework considering the connectivity and scalability between BIM and heterogeneous dataset. Through the proposed framework, ontology BIM mapping, semantic information query method for linking between knowledge-expressing dataset and BIM are presented. In addition, to identify the effectiveness of the proposed method, the prototype is developed. Also, the effectiveness and considerations of the ontology BIM-based knowledge service framework are derived.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.6-21
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• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.