Mining Supplier Relationships from Online News Documents
| Autor: | Hung-Yao Chen, 陳弘堯 |
|---|---|
| Rok vydání: | 2012 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 100 As the time past, the prosperity of a company is no longer just related to the performance of itself, or wins the competition with its competitor, but the success of its entire supply chain. The company must endeavor to consolidate the whole supply chain and make it thriving and prosperous. A company cannot just be viewed as a member of a single industry but as part of a business ecosystem that crosses a variety of industries. A company should have knowledge of and closely monitor its complete supply chain and ensure that all or most of the members of its supply chain well-functioning. It can be expected that a company must know about its customers and suppliers, but rarely know about the customers’ customers and the suppliers’ suppliers. In addition, the competition between two companies evolves to not just only companies go head-to-head in one industry, but supply chain versus supply chain or we can scale it up, business ecosystem versus business ecosystem. But as we know, the supplier information of a company is usually private. If a company wants to recognize the supply chains of other companies, it must be costly to investigate the business environment. When gathering business information, most of us rely on finance news. Business news documents often reveal various types of business events and relationships, including suppliers of companies. Thus, we want to mine the supplier information of a focal company from online news documents. We exploit text mining and data mining techniques to construct the model of supplier relationship mining (SRM) system. First, by using text mining approach, we can classify the news documents, and extract the sentences with supplier relationships, as well as the directions of supplier relationships (i.e., A company is a supplier of B company). With these results, the system can construct a supplier/customer graph. On the basis of supplier/customer graph, we develop 11 variables to support link assessment. Finally, we can get a refined supplier/customer graph. We propose a supplier relationship mining (SRM) system that automatically discovers the supplier relationships concerning a focal company from news documents and generate a supplier/customer graph of a focal company. Through the refinement, we can give the user more accurate supplier information of a focal company. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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