| 摘要 |
PURPOSE:To improve recognition efficiency by extracting candidates of interpretation for each data unit, calculating the certainty CF (Certainty Factor) of the candidates by using a correspondence rule and a possibility distribution table, extracting basis patterns, and discarding candidates which are not extracted as the basic patterns. CONSTITUTION:A data unit (processing unit) of each level is determined. Then candidates of interpretation are extracted for each data unit and the certainty CF of the candidates is calculated by using the correspondence rule which make candidate categories of low-order and high-order levels correspond to each other and the possibility distribution table where the level of the possibility of correspondence is digitized. This operation is carried out for each level from the low-order level to the high-order level and candidates with CF values less than a specific threshold value are discarded; and basic patterns are extracted for a candidate group which is remained up to the highest-order level and candidates which are not extracted as the basic patterns are discarded.
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