Resum
A new predictive support tool for the publishing industry is presented in this note. It consists of a combined model of Artificial Intelligence techniques (CAIT) that seeks the most optimal prediction of the number of book copies, finding out which is the best segmentation of the book market, using data from the networks social and the web. Predicted sales appear to be more accurate, applying machine learning techniques such as clustering (in this specific case, KMeans) rather than using current publishing industry expert’s segmentation. This identification has important implications for the publishing sector since the forecast will adjust more to the behavior of the stakeholders than to the skills or knowledge acquired by the experts, which is a certain way that may not be sufficient and/or variable throughout the period.
Idioma original | Anglès |
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Número d’article | 366 |
Revista | Applied Sciences (Switzerland) |
Volum | 12 |
Número | 1 |
DOIs | |
Estat de la publicació | Publicada - 1 de gen. 2022 |