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Strategy Based Interactive Value-Focused Thinking for Discovering the Future Chance

机译:基于策略的交互式价值关注思维,以发现未来机会

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When a customer needs information to make a good decision, he usually collects data from the internet. The cost of collecting data from the internet is very cheap which often makes him losing himself in the information. In this study the value-focused thinking (VFT)[41 method, which filtered out the invalid data and built the customer concerns associated relationships to visualize the text data, was used to avoid this kind of problem. This opportunity map helped him understand the information. We not only discovered the predictable opportunity based on the associated relationships, but also defined the rare opportunity according to the entropy of keywords'' link. The short wavelength laser diode as blue-ray, an important strategic factor, was considered as the important technology in the next generation according to the analyst''s experience. An associated map was built from a model based on the KeyGraph method using around 1000 DVD news collected from 1996 to 2004. Finally, according to the analyst''s demand both the strategic factor (blue-ray) and the links, connecting to other keywords in the associated map, were emerged in our model. As a result, "Toshiba'' was connected with the blue-ray, which meant "Toshiba'' had the chance to be the leader of DVD industry in the next generation. The events in the low occurring area were hardly discovered by previous methods. We proposed the entropy of keywords'' link and defined the rare opportunities, which has resulted the discovery of many rare but important keywords.
机译:当客户需要信息来做出明智的决定时,他通常会从互联网上收集数据。从互联网上收集数据的成本非常便宜,这常常使他迷失在信息中。在这项研究中,使用价值导向思维(VFT)[41]方法来过滤掉无效数据,并建立客户关注的关联关系以可视化文本数据,从而避免了此类问题。这次机会图帮助他了解了信息。我们不仅根据关联关系发现了可预测的机会,而且根据关键词链接的熵来定义了难得的机会。根据分析师的经验,作为蓝光的短波长激光二极管是重要的战略因素,被认为是下一代的重要技术。根据基于KeyGraph方法的模型,使用1996年至2004年收集的大约1000条DVD新闻构建了一个关联的地图。最后,根据分析人员的需求,战略因素(蓝光)和链接均与其他链接关联地图中的关键字出现在我们的模型中。结果,“东芝”与蓝光联系在一起,这意味着“东芝”有机会成为下一代DVD行业的领导者。以前的方法几乎没有发现低发区的事件。我们提出了关键词“熵”的链接,并定义了稀有机会,从而发现了许多稀有但重要的关键词。

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