Often when we think of the world of analysis, we always think of numerical experimental data that will then have to be somehow processed and then visualized on a graph. In reality, analysis has no prejudice regarding the type of “data to be analyzed”. This can be a simple number and an image, a sound, or even a text. And it is precisely the analysis of texts, and in particular of the language used, that we will discuss in this article. This article aims to exploit Python libraries that allow Language Processing and text analysis in general to extract the information of interest.
Extracting Information from Food-Related Textual Sources / Amato, A.; Bonavolonta, F.; Cozzolino, G.. - 227:(2021), pp. 72-80. [10.1007/978-3-030-75078-7_8]
Extracting Information from Food-Related Textual Sources
Bonavolonta F.;Cozzolino G.
2021
Abstract
Often when we think of the world of analysis, we always think of numerical experimental data that will then have to be somehow processed and then visualized on a graph. In reality, analysis has no prejudice regarding the type of “data to be analyzed”. This can be a simple number and an image, a sound, or even a text. And it is precisely the analysis of texts, and in particular of the language used, that we will discuss in this article. This article aims to exploit Python libraries that allow Language Processing and text analysis in general to extract the information of interest.| File | Dimensione | Formato | |
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Extracting-Information-from-FoodRelated-Textual-SourcesLecture-Notes-in-Networks-and-Systems.pdf
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