A statistical technique for bootstrapping available resources for proper nouns classification

Author

Cucchiarelli, Alessandro ; Velardi, Paola

Author_Institution

Ist. di Inf., Ancona Univ., Italy

fYear

1999

fDate

1999

Firstpage

429

Lastpage

435

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on

Conference_Location

Bethesda, MD

Print_ISBN

0-7695-0446-9

Type

conf

DOI

10.1109/ICIIS.1999.810312

Filename

810312