Browsing by Author "Hsu, Fu-Chiang"

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A Fuzzy Ontological Knowledge Document Clustering Methodology
(2009-06-01)
Trappey, Amy J. C.
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Trappey, Charles V.
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Hsu, Fu-Chiang
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Hsiao, David W.
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管理科學系
This correspondence presents a novel hierarchical clustering approach for knowledge document self-organization, particularly for patent analysis. Current keyword-based methodologies for document content management tend to be inconsistent and ineffective when partial meanings of the technical content are used for cluster analysis. Thus, a new methodology to automatically interpret and cluster knowledge documents using an ontology schema is presented. Moreover, a fuzzy logic control approach is used to match suitable document cluster(s) for given patents based on their derived ontological semantic webs. Finally, three case studies are used to test the approach. The first test case analyzed and clustered 100 patents for chemical and mechanical polishing retrieved from the World Intellectual Property Organization (WIPO). The second test case analyzed. and clustered 100 patent news articles retrieved from online Web sites. The third case analyzed and clustered 100 patents for radio-frequency identification retrieved from WIPO. The results show that the fuzzy ontology-based document clustering approach outperforms the K-means approach in precision, recall, F-measure, and Shannon's entropy.
Technology and knowledge document cluster analysis for enterprise R&D strategic planning
(2006)
Hsu, Fu-Chiang
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Trappey, Amy J. C.
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Trappey, Charles V.
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Hou, Jiang-Liang
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Liu, Shang-Jyh
Through technology and knowledge document analysis, companies can realise the condition of specified technology development and the potential competitors in the market. As patents provide exclusive right and legal protection for patent inventors, patents play an important role in the development of technology. This paper presents the process of patent knowledge extraction and methodologies of patent analysis to improve the efficiency of patent analysis. Furthermore, the methodologies proposed in this paper include patent map analysis, patent technology clustering, patent document clustering and technology maturity measurement. Through these methodologies, companies can gain rich information and perforin better in patent management. Moreover, the strategic plans of R&D can also be determined using the methodologies proposed in this paper.
Using Fuzzy Cognitive Map for Evaluation of RFID-based Reverse Logistics Services
(2009)
Trappey, Amy J. C.
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Trappey, Charles V.
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Wu, Chang-Ru
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Hsu, Fu-Chiang
;
管理科學系
Reverse logistics research is used to analyze the processes associated with the flows of products, components and materials from end users to re-users in different industries. The products and components collected for reverse logistics are often widely dispersed, which complicates efforts to efficiently collect, reuse and reassemble used components for reprocessing and remanufacturing. Therefore, Radio Frequency Identification (RFID) technology combined with the EPCglobal network architecture is applied to facilitate product and component data collection and data transmission. This research proposes a decision support model that integrates fuzzy cognitive maps trained using a genetic algorithm. The advantage of using fuzzy cognitive maps is that the model and the relationships among nodes (states) can be linguistically expressed both quantitatively and qualitatively. Furthermore, to diminish the subjective effects of the weights, the genetic algorithm is applied. The model and the information system integrate the EPCglobal network architecture with the RFID technology. Finally, a case concerning automobile repair reverse logistics is used to demonstrate the usefulness of the approach.