協同商務是個新興的概念，目前主要應用在製造業產品的生產、設計及行銷等方面，對於提供數位知識內容服務為主的證券業而言，如能透過協同商務來結合其協同價值鏈，將能提供更豐富的理財資訊及更簡便的交易服務。故我們以理財資訊產品為基礎，提出證券服務業的協同模式。在本論文中並針對其中最富挑戰性的理財資訊分析技術，做深入的探討。雖然已有許多的理財資訊分析技術被應用於電腦選股這個研究領域中，但一般民眾對於電腦的預測原理既不了解也不信賴，有鑑於傳統電腦選股方法的預測模型無法滿足大眾要求，故本論文嘗試以國內民眾較熟悉的股市專家建議作切入點，利用資料採礦技術來探討專家建議與股價變化間的關聯性。藉著這些關聯性，我們除了可以得到容易為一般民眾接受的建議，更可以衡量比對電腦選股系統的結果，以對其預測模型做出解釋。本論文從網站上取得股市專家的研究報告，對其內容加以數值化及離散化，再以資料採礦技術來分析。透過我們的方法可以得知，對國內的股票市場而言，專家的評論資訊對股價有所影響，值得我們去加以探討。 Collaborative commerce is an emerging concept. It is mostly applied in production, design and sale of the manufacturing industry today. Based on this platform, we build a new collaborative value chain for stock investment by the service chain of digital knowledge content. The analysis of financial information for supporting stock investment is further discussed in this thesis. Many computer techniques have been proposed for stock investment. However, in Taiwan, most of investors neither understand nor believe these prediction results. They usually take research reports from securities firms or expertise from stock experts in investing stock. In this thesis, we use data mining techniques to find the relationship between expert knowledge and stock price where the expert knowledge is collected from research reports of securities firms. Based on the mining results, we can find investment suggestions that are more acceptable for the general public.
