Expert Systems with Applications , 34 (2), 2008 – interesting articles
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(German title: Expert Systems with Applications , 34 (2), 2008 – interessante Artikel)

A hybrid knowledge and model approach for reviewer assignment 817-824
Yong-Hong Sun, Jian Ma, Zhi-Ping Fan and Jun Wang

  • Abstract: In R&D project selection, experts (or external reviewers) always play a very important role because their opinions will have great influence on the outcome of the project selection. It is also undoubted that experts with high expertise level will make useful and professional judgments on the projects to be selected. So, how to assign the most appropriate experts to the relevant proposals is a very significant issue. This paper presents a hybrid knowledge and model approach which integrates mathematical decision models with knowledge rules, for the assignment of external reviewers to R&D project proposals. The approach can be applied to government funding agencies in China and other countries.
  • Keywords: Decision support systems; Knowledge-based systems; R&D project selection; Assignment problem
  • doi: 10.1016/j.eswa.2006.10.021 

Dynamic EMCUD for knowledge acquisition 833-844
Shun-Chieh Lin, Shian-Shyong Tseng and Chia-Wen Teng

  • Abstract: Due to the knowledge explosion, the new objects will be evolved in a dynamic environment. Hence, the knowledge can be classified into static knowledge and dynamic knowledge. Although many knowledge acquisition methodologies, based upon the Repertory Grid technique, have been proposed to systematically elicit useful rules from static grid from domain experts, they lack the ability of grid evolution to incrementally acquire the dynamic knowledge of new evolved objects. In this paper, we propose dynamic EMCUD, a new Repertory Grid-based knowledge acquisition methodology to elicit the embedded meanings of knowledge (embedded rules bearing on m objects and k object attributes), to enhance the ability of original EMCUD to iteratively integrate new evolved objects and new added attributes into the original Acquisition Table (AT) and original Attribute Ordering Table (AOT). The AOT records the relative importance of all attribute to each object in EMCUD to capture the embedded meanings with acceptable certainty factor value by relaxing or ignoring some minor attributes. In order to discover the new evolved objects, a collaborative framework including local knowledge based systems (KBSs) and a collaborative KBS is proposed to analyze the correlations of inference behaviors of embedded rules between multiple KBSs in a dynamic environment. Each KBS monitors the frequent inference behaviors of interesting embedded rules to construct a small AT increment to facilitate the acquisition of dynamic knowledge after experts confirming the new evolved objects. Moreover, the significance of knowledge may change after a period of time, a trend of all attributes to each evolved object is used to construct a new AOT increment to help experts automatically adjust the relative importance of each attribute to each object using time series analysis approach. Besides, three cases are considered to assist experts in adjusting the certainty factor values of the dynamic knowledge of the new evolved objects from the collection of inference logs in the collaborative KBS. To evaluate the performance of dynamic EMCUD in incrementally integrating new knowledge into the knowledge base, a worm detection prototype system is implemented.
  • Keywords: Knowledge acquisition; Dynamic EMCUD; Dynamic knowledge; Trend analysis; Worm detection
  • doi: 10.1016/j.eswa.2006.10.041 

KBSLUA: A knowledge-based system applied in river land use assessment 889-899
Tzai-Zang Lee, Chien-Hsing Wu and Hsien-Hui Wei

  • Abstract: The assessment of river land use is an important, but complex and time-consuming task that has to deal with a huge amount of data, domain regulations, legal aspects, and expert knowledge in terms of environmental protection, ecology, and water resource reuse. This paper presents a knowledge-based system (KBSLUA) that is used to help the assessment of development plans for river land use. A salient function of the KBSLUA is its user interface, which utilizes the functions of an existing geographic information system to retrieve geographic data as the inputs of assessment activities. Decision tables are used to acquire expert knowledge, and a forward chaining inference mechanism is utilized to derive assessment suggestions and assessment results. Two test cases are used to demonstrate the proposed KBSLUA.
  • Keywords: Knowledge-based system; River land use; Geographic information system
  • doi: 10.1016/j.eswa.2006.10.038

Knowledge discovery in financial investment for forecasting and trading strategy through wavelet-based SOM networks 935-951
Sheng-Tun Li and Shu-Ching Kuo

  • Abstract: The stock market has been a popular financial investment channel in the recent era of low interest rates. How to maximize profits is always the main concern for investors; and different investors have different preferences about the holding periods of their investments. In this study, in contrast to other related studies, we propose a hybrid approach on the basis of the knowledge discovery methodology by integrating K-chart technical analysis for feature representation of stock price movements, discrete wavelet transform for feature extraction to overcome the multi-resolution obstacle, and a novel two-level self-organizing map network for the underlying forecasting model. In particular, a visual trajectory analysis is conducted to reveal the relationship of movements between primary bull and bear markets and help determine appropriate trading strategies for short-term investors and trend followers. The forecasting accuracy and trading profitability of the proposed decision model is validated by performing experiments using the Taiwan Weighted Stock Index (TAIEX) from 1991 to 2002 as the target dataset. The resultant intelligent investment model can help investors, fund managers and investment decision-makers of national stabilization funds make profitable decisions.
  • Keywords: Knowledge discovery; Self-organizing map network; Wavelet transform; Financial investment; Trajectory analysis
  • doi: 10.1016/j.eswa.2006.10.039

Integrating intra-firm and inter-firm knowledge diffusion into the knowledge diffusion model 1423-1433
Chih Ming Tsai

  • Abstract: Knowledge value and enterprise benefits are closely related. The performance of a knowledge management system can be evaluated when the dynamic relationship between knowledge value and its corresponding enterprise benefits is identified quantitatively. This study introduces five kinds of knowledge diffusion patterns, including knowledge internalization, knowledge externalization, knowledge improvement, external knowledge acquisition, and internal knowledge release, to construct the knowledge diffusion model which integrates the intra-firm and inter-firm diffusion processes simultaneously. An illustrative case demonstrates the feasibility of the proposed model successfully. In addition to the estimation of all parameters involved in the model, the parameter analysis provides some managerial insights into the implementation of the knowledge management system. Therefore, it follows that knowledge can be managed more effectively, and as a result the appropriate knowledge strategies can also be established for enhancing competitiveness.
  • Keywords: Knowledge diffusion model; Intra-firm knowledge diffusion; Inter-firm knowledge diffusion; Knowledge value; Enterprise benefits
  • doi: 10.1016/j.eswa.2007.01.027 

Automatic expert identification using a text categorization technique in knowledge management systems 1445-1455
Kun-Woo Yang and Soon-Young Huh

  • Abstract: Since tacit knowledge such as know-how and experiences is hard to be managed effectively using information technology, it is recently proposed that providing an appropriate expert identification mechanism in KMS to pinpoint experts in the organizations with searched expertise is more effective and efficient to utilize this type of knowledge. In this paper, we propose a framework to automate expert identification using a text categorization technique called Vector Space Model to minimize maintenance cost of expert profiles as well as problems related to incorrectness and obsolescence resulted from subjective manual profile processing. Also, we define the structure of expertise consisting of activeness, relevance, and usefulness factors to enable deriving the overall expertise level of experts by analyzing knowledge artifacts registered to the knowledge base. The developed prototype system, “Knowledge Portal for Researchers in Science and Technology”, is introduced to show the applicability of the proposed framework.
  • Keywords: Expert identification; Knowledge management system; Text categorization; Portal
  • doi: 10.1016/j.eswa.2007.01.010  

The effect of knowledge sharing model 1508-1521
Wen-Bao Lin

  • Abstract: Three elements – organizational structure characteristics, organizational culture, and interunit interaction – that affect knowledge sharing are raised in this study based on the structure of organization theories and the interaction among units of an organization. By carrying out empirical research on five hi-tech industries in Taiwan and verifying hypotheses with the non-linear fuzzy neural network model, this study finds that the lower the formalization of an organizational structure is, the greater the knowledge sharing among units of an organization will be, while the higher the complexity of an organizational structure is, the lower the knowledge sharing among units of an organization will be. Trust and commitment among units are important for facilitating knowledge sharing among units, and creative and supporting characteristics of organizational culture are beneficial for the implementation of knowledge sharing activities.
  • Keywords: Organizational culture; Organizational structure characteristics; Trust; Commitment; Knowledge sharing
  • doi: 10.1016/j.eswa.2007.01.015 

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