Title :
A statistical technique for bootstrapping available resources for proper nouns classification
Author :
Cucchiarelli, Alessandro ; Velardi, Paola
Author_Institution :
Ist. di Inf., Ancona Univ., Italy
Abstract :
Describes an algorithm for improving the performance of unknown proper noun recognizers, using a statistical framework. We present a bootstrapping technique that starts out by using a training set to acquire contextual classification cues, and then uses the results of the initial phase to acquire additional training data from an unlabeled corpus. The training set (tagged proper nouns in contexts) is obtained trough an application of standard knowledge-based techniques for proper noun tagging, commonly used in information extraction systems
Keywords :
context-sensitive grammars; learning (artificial intelligence); natural languages; pattern classification; bootstrapping; contextual classification cues; information extraction systems; proper noun tagging; proper nouns classification; standard knowledge-based techniques; statistical technique; training set; unlabeled corpus; Data mining; Dictionaries; Electronic mail; Information systems; Remuneration; Tagging; Telephony; Text recognition; Thesauri; Training data;
Conference_Titel :
Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on
Conference_Location :
Bethesda, MD
Print_ISBN :
0-7695-0446-9
DOI :
10.1109/ICIIS.1999.810312
