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.
Content-based image retrieval (CBIR) has been adopted as a complementary technique to the keyword-based image search. Relevance feedback (RFB) is considered as an effective means to bridge the gap between the designated features and the run-time semantics on a CBIR system. Like many other interactive system, a good
matching RDF triples instead of keywords. The results of the experiments performed on our framework showed improvements in precision and recall compared to the existing semantic-based information retrieval techniques.
With rapid development of Internet information, It is quite an important project for data mining that how to classify these large amounts of texts. In this paper, we propose an improved text classify cluster algorithm, while calculating similarity, we synthetically consider the relationship between keywords and
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.