Using open data and Google search data for competitive intelligence analysis

Pub Date : 2019-11-13 DOI:10.37380/jisib.v9i2.470
Jan Černýa, Martin Potančoka, Zdeněk Molnára
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引用次数: 2

Abstract

Open data are information entities that are of significant importance for many institutions, businesses and even citizens as the part of the digital transformation within many fields in our society. The aim of this paper is to provide a competitive environment analysis method using open source intelligence within the pharmaceutical sector and to design the optimal data structure for this purpose. Firstly, we have described the state-of-the-art of open human medicine data within the European Union with a focus on antidepressants and we have chosen the Czech Republic as the primary research territory for demonstrating competitive intelligence analysis. Secondly, we have identified the competitive intelligence and open source intelligence relationship with a new possible contextual analysis method using open human medicine data and Google Search data. Finally, this paper shows the potential of open deep web data within competitive intelligence activities, together with surface web data entities as a lowcost approach with high intelligence value focused on the pharmaceutical market.
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利用开放数据和谷歌搜索数据进行竞争情报分析
开放数据是对许多机构、企业甚至公民具有重要意义的信息实体,是我们社会许多领域数字化转型的一部分。本文的目的是在制药行业中使用开源智能提供一种竞争环境分析方法,并为此设计最佳数据结构。首先,我们描述了欧盟最先进的开放人类医学数据,重点是抗抑郁药,我们选择捷克共和国作为展示竞争情报分析的主要研究领域。其次,我们利用开放的人类医学数据和谷歌搜索数据,用一种新的可能的上下文分析方法确定了竞争情报和开源情报的关系。最后,本文展示了开放式深度网络数据在竞争情报活动中的潜力,以及表面网络数据实体作为一种低成本、高智能价值的方法,专注于制药市场。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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