Intelligent Classification of Economic Activities from Free Text Descriptions

Elias OliveiraPatrick Marques CiarelliWallace F. HenriqueLucas VeroneseFelipe PedroniAlberto F. De Souza

We tackle the problem of automating the categorization of economic activities from business descriptions in free text format. This kind of information is vital to fundamental aspects of national governmental administration such as short, medium and long term planning and taxation. As the number of possible categories considered is very large (more than 1000 in the Brazilian scenario), the automatic text categorization problem targeted here is quite challenging. We have applied and compared the use of two different techniques to deal with it: the Vector Space Model in its classical form to represent the texts, and VG-RAM, a Weightless Neural Network.

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