This paper describes SIE (Simple Information Extraction), a modular information extraction system designed with the goal of being easily and quickly portable across tasks and domains. SIE is composed bya general purpose machine learning algorithm(SVM) combined with several customizable modules. A crucial role in the architecture is played by Instance Filtering,which allows to increase efficiency without reducing effectiveness. The results obtained by SIE on several standard data sets, representative of different tasks and domains, are reported. The experiments show that SIE achieves performance close to the best systems in all tasks, without using domain-specific knowledge.



Titolo: Simple Information Extraction (SIE): A Portable and Effective IE System
Autori: 
Giuliano, Claudio
Lavelli, Alberto
Romano, Lorenza
Data di pubblicazione: 2006
Abstract: This paper describes SIE (Simple Information Extraction), a modular information extraction system designed with the goal of being easily and quickly portable across tasks and domains. SIE is composed bya general purpose machine learning algorithm(SVM) combined with several customizable modules. A crucial role in the architecture is played by Instance Filtering,which allows to increase efficiency without reducing effectiveness. The results obtained by SIE on several standard data sets, representative of different tasks and domains, are reported. The experiments show that SIE achieves performance close to the best systems in all tasks, without using domain-specific knowledge.
Handle: http://hdl.handle.net/11582/2771
Appare nelle tipologie:4.1 Contributo in Atti di convegno

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