An Active Ingredients Entity Recogniser System Based on Profiles.

This paper describes an active ingredients named entity recogniser. Our machine learning system, which is language and domain independent, employs unsupervised feature generation and weighting from the training data. The proposed automatic feature extraction process is based on generating a profile for the given entity without traditional knowledge resources (such as dictionaries). Our results (F1 87.3 % [95 %CI: 82.07–92.53]) proves that unsupervised feature generation can achieve a high performance for this task.

Autores: 
Moreno, Isabel
Moreda, Paloma
Romá-Ferri, M.T.
Tipo de publicación: 
Acta de congreso
Nombre de la revista: 
Natural Language Processing and Information Systems
Nombre del libro: 
-
Subtítulo: 
NLDB 2016
Volumen: 
9612
Revisión por pares: 
Internacional: 
Título de la serie: 
Lecture Notes in Computer Science
Editorial: 
Springer, Cham
Publicable: 
DOI: 
10.1007/978-3-319-41754-7_25
Año de publicación: 
2 016