The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In text classification, dimension reduction on the original features space is very necessary to improve accuracy and efficiency. Feature selection is a kind of simple and effective methods in dimension reduction. In this paper, we designed two feature selection methods based on the feature's category discriminability (CD) and the influence of features cooccurrence to classification. The experiment...
Data dimension reduction plays an important role in the field of text representation. An effective dimension reduction method can not only reduce computation complexity, but help to improve the accuracy of text classification. This paper presents a new method of dimension reduction which is based on words semantic similarities. Being different with traditional methods which usually use the statistical...
In this paper we take our effort to achieve a fast and accurate classifier: a BVB (BAM-Vote Box)-based framework is presented for text categorization by using ensemble method. The central idea is that combining two-class classifications for the multi-class tasks. This framework generates associating terms and extending the set of basis element, and includes a feature selection method, which can reduce...
Feature selection is a valid method to reduce the dimension of vector in text categorization system. After analyzed several common evaluation functions for feature selection, we applied terms weight function to feature selection. A new evaluation function based on improved TFIDF method is presented; in this function the category information is introduced to feature items, and the feature items of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.