An unsupervised segmentation/clustering algorithm is a method for modeling the generation of directly observable visible variables from hidden sources. Each hidden source coop- erates in activating a subset of visible variables, or parts, which, in turn, additively generate the whole. This project aims at applying the versatility of such a method to the semantic analysis of text documents, namely patent applications.
Unsupervised algorithms as a new tool for reclassification and indexing of European Patent Office documents.
Massimo Ladisa
2022
Abstract
An unsupervised segmentation/clustering algorithm is a method for modeling the generation of directly observable visible variables from hidden sources. Each hidden source coop- erates in activating a subset of visible variables, or parts, which, in turn, additively generate the whole. This project aims at applying the versatility of such a method to the semantic analysis of text documents, namely patent applications.File in questo prodotto:
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