The effects of integrating XBRL and clustering on the disclosure financial reports

• Main Authors: Wu tsung lin, 吳宗霖
• Other Authors: Hsu jung lung
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/29899848322734365531

碩士 === 開南大學 === 資訊及電子商務學系 === 102 === It’s change quickly in the stock market today, it’s can be effect by everything, so predict how do it change is a good issue to research , now many country in the world are using XBRL for financial statements , using XBRL can more faster get the accountancy information which you want , and few research combine XBRL and Data Mining , so it’s have much benefit to research , in this research we use weak API analysis by clustering algorithms and combine Google App Engine develop on the network , and show the result by chart , according to the research , every company’s large amounts of data can analysis for few minute by this system , because of XBRL’s data is large and Complete , and it can get on the network for free , and it’s dedicated for financial statements , so XBRL is more suitable on analysis than other data , in this research we don’t have much effect on stock price prediction , so we suggest try use other algorithms and combine text mining collect some news for stock to strengthen this system .