Noise reduction in a statistical approach to text categorization
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
| Hi-index | 0.00 |
The precision and efficiency of the similarity computing of documents is the foundation and key of other documents processing. In this paper, the DF and TF-IDF algorithms are improved. First, DF's time complexity is linear which suits mass documents processing, but it has the fault that exceptional useful features may be deleted, so we make up that by adding the count of the words at the important places. Second, we rectify the weight of feature by the result of feature selection phase. In this way, we improve the precision of documents similarity without adding much time and space complexity.