Adjusting a hidden Markov model tagger for sentence fragments
US5822731A · kind A · utility
Assignee
Inventor
Key dates
| Filing date | Sep 15, 1995 |
| Grant date | Oct 13, 1998 |
| Priority date | — |
| Expiry date | Sep 15, 2015 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/216
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for parsing information representative of a sequence of words having parts of speech. The sequence of words forms a sentence or sentence fragment. A hidden Markov model is provided for determining the most likely part of speech of a selected word of the sequence of words. The hidden Markov model has an initial transition matrix and a subsequent transition matrix for storing probabilities of occurrence of the parts of speech. The initial transition matrix of the hidden Markov model is removed to provide a modified hidden Markov model. The modified hidden Markov model is applied to the sequence of words to determine the most likely part of speech of a selected word within a sentence fragment with increased accuracy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.