Method for predicting negative example, system for detecting incorrect wording using negative example prediction

A computer readable medium storing an executable code to perform on a computer a method of determining whether input data is correct, the method comprising:

• storing a positive example data group D, including a number n of positive examples, wherein a positive example is known to be a correct example;
• selecting example data x from the input data, which example data x consists of two independent parts a and b;
• determining whether the example data x is stored in the positive example data group D;
• calculating probabilities P(a) and P(b) based on appearance of part a and of part b of the example data x, respectively, in the positive example data group D, when the example data x is not stored in the positive example data group D, and determining a first probability P(x)=P(a)·P(b) that the example data x should be stored as a positive example in the positive example data group D;
• and
• estimating a likelihood that the example data x is a negative example, any negative example being purposefully excluded from the positive example data group D, by calculating a second probability Q(x) using the first probability P(x), wherein Q(x)=1−(1−P(x))n the second probability representing likelihood that the example data x should be stored as any one of n positive examples in the positive example data group D when the example data x is not currently stored as a positive example;
• determining the example data x is a negative example, if the second probability is larger than a predetermined value and the example data x is not currently stored as a positive example, and
• outputting the example data x if the determining indicated that the example data x is a negative example.