Textual Event Detection Using Fuzzy Fingerprints

Autor:	David Martins de Matos, Anatole Gershman, João Paulo da Silva Neto, Luís Marujo, João Carvalho, Jaime G. Carbonell
Rok vydání:	2015
Předmět:	Support vector machine business.industry Computer science Pattern recognition Artificial intelligence business Value (mathematics) Fuzzy logic Event (probability theory) Random forest
Zdroj:	Advances in Intelligent Systems and Computing ISBN: 9783319113128 IEEE Conf. on Intelligent Systems (1)
DOI:	10.1007/978-3-319-11313-5_72
Popis:	In this paper we present a method to improve the automatic detection of events in short sentences when in the presence of a large number of event classes. Contrary to standard classification techniques such as Support Vector Machines or Random Forest, the proposed Fuzzy Fingerprints method is able to detect all the event classes present in the ACE 2005 Multilingual Corpus, and largely improves the obtained G-Mean value.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0c99c551c954528fc0967093cd952685 https://doi.org/10.1007/978-3-319-11313-5_72 Zobrazit plný text záznamu