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Journal Articles Journal of Intelligent Information Systems Year : 2016

A framework for enriching Data Warehouse analysis with Question Answering systems

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Alejandro Mate
  • Function : Author
  • PersonId : 1024247
Jesus Peral
  • Function : Author
  • PersonId : 1060414
Juan Trujillo
  • Function : Author
  • PersonId : 1024248

Abstract

Business Intelligence (BI) applications allow their users to query, understand, and analyze existing data within their organizations in order to acquire useful knowledge, thus making better strategic decisions. The core of BI applications is a Data Warehouse (DW), which integrates several heterogeneous structured data sources in a common repository of data. However, there is a common agreement in that the next generation of BI applications should consider data not only from their internal data sources, but also data from different external sources (e.g. Big Data, blogs, social networks, etc.), where relevant update information from competitors may provide crucial information in order to take the right decisions. This external data is usually obtained through traditional Web search engines, with a significant effort from users in analyzing the returned information and in incorporating this information into the BI application. In this paper, we propose to integrate the DW internal structured data, with the external unstructured data obtained with Question Answering (QA) techniques. The integration is achieved seamlessly through the presentation of the data returned by the DW and the QA systems into dashboards that allow the user to handle both types of data. Moreover, the QA results are stored in a persistent way through a new DW repository in order to facilitate comparison of the obtained results with different questions or even the same question with different dates.

Dates and versions

hal-02402487 , version 1 (10-12-2019)

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Cite

Antonio Ferrandez, Alejandro Mate, Jesus Peral, Juan Trujillo, Elisa de Gregorio, et al.. A framework for enriching Data Warehouse analysis with Question Answering systems. Journal of Intelligent Information Systems, 2016, 46 (1), pp.61-82. ⟨10.1007/s10844-014-0351-2⟩. ⟨hal-02402487⟩
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