Title :
Combining finite state automata and a greedy learning algorithm to determine the syntactic roles of commas
Author :
Van Delden, Sebastian ; Gomez, Fernando
Author_Institution :
Dept. of Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
Abstract :
A method has been developed and implemented that assigns syntactic roles to commas. Text that has been tagged using a part-of-speech tagger serves as the input to the system. A set of Finite State Automata first assigns temporary syntactic roles to each comma in the sentence. A greedy learning algorithm is then used to determine the final syntactic roles of the commas. The system requires no training and is not domain specific. The performance of the system on numerous corpora is given.
Keywords :
computational linguistics; finite state machines; learning (artificial intelligence); natural languages; finite state automata; greedy learning; natural languages; part-of-speech tagger; syntactic roles; syntactic roles of commas; Learning automata; NASA; Natural languages; Speech; Tagging;
Conference_Titel :
Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. 14th IEEE International Conference on
Print_ISBN :
0-7695-1849-4
DOI :
10.1109/TAI.2002.1180817