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n-Gram Statistics for Natural Language Understanding and Text Processing

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1 Author(s)
Suen, Ching Y. ; SENIOR MEMBER, IEEE, Department of Computer Science, Concordia University, Montreal, P.Q., Canada; Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.

n-gram (n = 1 to 5) statistics and other properties of the English language were derived for applications in natural language understanding and text processing. They were computed from a well-known corpus composed of 1 million word samples. Similar properties were also derived from the most frequent 1000 words of three other corpuses. The positional distributions of n-grams obtained in the present study are discussed. Statistical studies on word length and trends of n-gram frequencies versus vocabulary are presented. In addition to a survey of n-gram statistics found in the literature, a collection of n-gram statistics obtained by other researchers is reviewed and compared.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-1 ,  Issue: 2 )