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Detecting weak signals for long-term business opportunities using text mining of Web news

机译:使用网络新闻的文本挖掘来检测长期业务机会的微弱信号

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摘要

In an uncertain business environment, competitive intelligence requires peripheral vision to scan and identify weak signals that can affect the future business environment. Weak signals are defined as imprecise and early indicators of impending important events or trends, which are considered key to formulating new potential business items. However, existing methods for discovering weak signals rely on the knowledge and expertise of experts, whose services are not widely available and tend to be costly. They may even provide different analysis results. Therefore, this paper presents a quantitative method that identifies weak signal topics by exploiting keyword-based text mining. The proposed method is illustrated using Web news articles related to solar cells. As a supportive tool for the expert-based approach, this method can be incorporated into long-term business planning processes to assist experts in identifying potential business items.
机译:在不确定的商业环境中,竞争情报需要外围视觉来扫描和识别可能影响未来商业环境的微弱信号。弱信号被定义为即将发生的重要事件或趋势的不精确和早期指标,被认为是制定新的潜在业务项目的关键。但是,发现微弱信号的现有方法依赖于专家的知识和专业知识,他们的服务尚不广泛,而且价格昂贵。他们甚至可能提供不同的分析结果。因此,本文提出了一种利用基于关键字的文本挖掘来识别弱信号主题的定量方法。使用与太阳能电池相关的网络新闻文章对提出的方法进行了说明。作为基于专家的方法的支持工具,可以将该方法结合到长期业务计划流程中,以帮助专家确定潜在的业务项目。

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