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.
) preferences of the user with respect to a set of keywords. These preferences may then be used to rank the daily news, so that the user is recommended those items that match better with his/her interests. The cyclic preference learning methodology described in this paper is illustrated with a case example based on real news from
In a time when volatile data is in constant growth, the importance of keyword extraction becomes particularly evident. Keywords can quickly identify, structure and reveal potentially worthwhile information. The quality of automatically extracted keywords reflects the individual characteristics of the various retrieval
Since keyword-based search engine usually return large amount of results in which there are many unrelated documents and many documents with same content, automatic clustering technology is used to classify the retrieval results. While there are large amount of Web retrieval results, the clustering process usually
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.