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.
Representation learning has emerged as a newly active research subject in many machine learning applications because of its excellent performance. In the context of natural language processing, paragraph (or sentence and document) embedding learning is more suitable/reasonable for some tasks, such as information retrieval and document summarization. However, as far as we are aware, there is only a...
Extractive summarization aims at selecting a set of indicative sentences from a source document as a summary that can express the major theme of the document. A general consensus on extractive summarization is that both relevance and coverage are critical issues to address. The existing methods designed to model coverage can be characterized by either reducing redundancy or increasing diversity in...
Representation learning has emerged as a newly active research subject in many machine learning applications because of its excellent performance. As an instantiation, word embedding has been widely used in the natural language processing area. However, as far as we are aware, there are relatively few studies investigating paragraph embedding methods in extractive text or speech summarization. Extractive...
Extractive speech summarization attempts to select a representative set of sentences from a spoken document so as to succinctly describe the main theme of the original document. In this paper, we adapt the notion of risk minimization for extractive speech summarization by formulating the selection of summary sentences as a decision-making problem. To this end, we develop several selection strategies...
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.