Publications

@phdthesis{alegre_supervised_2019,

title = {SUPERVISED MACHINE LEARNING FOR CLASSIFICATION, MINING, AND RANKING OF ILLEGAL WEB CONTENTS},

author = {Enrique Alegre},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=es&user=yATJZvcAAAAJ&cstart=100&pagesize=100&sortby=title&citation_for_view=yATJZvcAAAAJ:ldfaerwXgEUC},

year  = {2019},

date = {2019-01-01},

school = {UNIVERSITY OF LEÓN},

abstract = {This thesis introduces algorithms, methods, and datasets aimed at classifying, mining information, and ranking web domains or similar resources containing text. The focus is on detecting web content that may indicate illegal activities, particularly in the Tor Darknet and Online Notepad Services (ONS), like Pastebin. Motivated by a collaboration with INCIBE, the research addresses the identification of criminal content in these areas, based on the assumption that the Tor network harbors a significant amount of illicit activity.},

keywords = {Darknet, Illegal Activities, Pastebin, Text classification, TOR Network},

pubstate = {published},

tppubtype = {phdthesis}

}