An Ontology-based Competitive Intelligence to facilitate AHP modeling
碩士 === 中原大學 === 資訊管理研究所 === 95 === This study proposed ontology-based competitive intelligence (CI) for on-line news classification. That can be applied to AHP(Analytical Hierarchy Process)-based decision support system. Quantitative data or structure data is the most common way for decision-making....
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/19718440640004209579 |
| Summary: | 碩士 === 中原大學 === 資訊管理研究所 === 95 === This study proposed ontology-based competitive intelligence (CI) for on-line news classification. That can be applied to AHP(Analytical Hierarchy Process)-based decision support system. Quantitative data or structure data is the most common way for decision-making. Computer system has not much ability to process qualitative data or unstructured data such as on-line news. There is more valuable information inside on-line news for decision-making. Information overload is the problem of on-line news. Usually, Keywords-matching is used to solve this kind of problem, but the results at the end are not good enough to satisfy user’s mind. According to the above situation, this study proposed ontology-based competitive intelligence (CI) for on-line news classification. The first step is to sort the interrelated news using Filtering-Ontology. The second step is to decompose the news into the structure information for supporting AHP system with Decision-Ontology. Decision-Ontology is composed of AHP factors in good news or bad news. Mind Mapping and Formal Concept Analysis are used for extracting knowledge from domain expert. We use the case study of stock investment. The results show that the process of ontology-based news classification could transform news into competitive intelligence for AHP-based decision-making.
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