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Decision Support in Mutual Fund Investment Based on Internet Derived Data

机译:基于互联网衍生数据的共同基金投资决策支持

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Data mining is a set of methods for extracting previously unknown, incomprehensible, and unactionable information from a large database, and using it to make critical business decisions. Data mining is often used in the knowledge discovery process to distinguish previously unknown relationships and patterns within data. Specifically, it is applied to a large database. In many cases, the data sets found on the World Wide Web are derived or processed data that usually can be used for decision support directly. An investment company without a fixed capitalization that purchases shares in numerous enterprises and issues its own shares for public sale provides a mutual fund. The investment profit of mutual funds is evenly distributed to each shareholder. The stock prices in the market are dynamic fluctuating every moment. The information recorded and published today is coutdated for tomorrow's market. Therefore, the Internet is an ideal place to record stock market activities and to provide updated information for its audiences.
机译:数据挖掘是用于从大型数据库中提取以前未知,难以理解且无法操作的信息,并使用它来制定关键业务决策的一组方法。在知识发现过程中经常使用数据挖掘来区分数据中以前未知的关系和模式。具体来说,它适用于大型数据库。在许多情况下,在万维网上找到的数据集是衍生或处理的数据,通常可以直接用于决策支持。没有固定资本的投资公司购买众多企业的股票并发行自己的股票以公开发售,就可以提供共同基金。共同基金的投资收益平均分配给每个股东。市场中的股票价格每时每刻都在动态波动。今天记录和发布的信息适合明天的市场。因此,Internet是记录股票市场活动并为其受众提供更新信息的理想场所。

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