Abstract
As information becomes more and more abundant and accessible on the web, researchers do not have to dig through books and libraries. Web pages are rich in textual information, the web search engines provide Internet users with various files corresponding to the searched keywords. This large number of digital data makes manual sorting difficult to do, so it is necessary to automate collection of useful information using techniques based on artificial intelligence. In today’s digital age, great importance is given to information retrieval techniques via Internet. Therefore, it appears essential to preconize a credible and performing system dealing with all textual information, in order to deduce structured and useful knowledge. This work focuses on four models used in the field of information retrieval, and highlights their limits of use, with a view to developing new techniques that can fill the gaps detected. At the end, the evaluation parameters will be discussed to enhance human intervention in decision making.
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El Hassani, M., Falih, N. (2021). The Search for Digital Information by Evaluating Four Models. In: Fakir, M., Baslam, M., El Ayachi, R. (eds) Business Intelligence. CBI 2021. Lecture Notes in Business Information Processing, vol 416. Springer, Cham. https://doi.org/10.1007/978-3-030-76508-8_8
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DOI: https://doi.org/10.1007/978-3-030-76508-8_8
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