Text retrieval algorithm that decreases confusion

To overcome the problem that the confusion between texts limits the precision in text retrieval, a new text retrieval algorithm that decrease confusion (DCTR) is proposed. The algorithm constructs the searching template to represent the user's searching intention through positive and negative training. By using the prior probabilities in the template, the supported probability and anti-supported probability of each text in the text library can be estimated for discrimination. The searching result can be ranked according to similarities between retrieved texts and the template. The complexity of DCTR is close to term frequency and mversed document frequency (TF-IDF). Its distinguishing ability to confusable texts could be advanced and the performance of the result would be improved with increasing of training times.