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Visualizing Large Graphs Out of Unstructured Data for Competitive Intelligence Purposes

Abstract : In the information era, people’s lives are deeply impacted by IT via exposure to social media, emails, RSS feed, chats, web pages, etc. Such data is considered very valuable nowadays since it may help companies to better their strategies. For example, companies can analyse their customers’ trends or their competitors marketing interventions and adjust their strategies accordingly. Several decisional tools have been developed but most of them rely on relational databases. This makes it difficult for decision makers to take advantage of unstructured data which today represents more than 85% of the available data. Thus, there is a rising need for a suitable management process of unstructured data through collecting, managing, transferring and transforming it into a meaningful informed data. This paper will introduce a new tool for Big Unstructured Data for the Competitive Intelligence named Xplor EveryWhere (XEW). It will also describe the enhancement brought to its newest feature XEWGraph. This tool, or as described later on the paper, this “Service”, offers the decision makers the possibility to have a better user experience regarding large graph visualization on their web browsers as well as their mobile devices.
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Submitted on : Monday, June 8, 2020 - 11:44:17 AM
Last modification on : Wednesday, June 9, 2021 - 10:00:30 AM


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  • HAL Id : hal-02860065, version 1
  • OATAO : 22136


Zakaria Boulouard, Lahcen Koutti, Nihal Chouati, Amine El Haddadi, Bernard Dousset, et al.. Visualizing Large Graphs Out of Unstructured Data for Competitive Intelligence Purposes. SAI Intelligent Systems Conference (IntelliSys 2016), Sep 2016, London, United Kingdom. pp.605-626. ⟨hal-02860065⟩



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