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.
To reduce the human effort in labeling the training set for document classification, some learning algorithms ask users to give the representative keywords for each class rather than any labeled documents. The key challenge in such \emph {keyword-labeled classification} is how to learn the high quality classifier with
Keywords can be considered as condensed versions of documents, which can play important role in some text processing tasks such as text indexing, summarization and categorization. However, there are many digital documents especially on the Internet that do not have a list of assigned keywords. Assigning keywords to
This paper presents a method for generating indexable and browsable keyword metadata from ASR transcripts by leveraging theWeb. Search engine queries are built from an ASR transcript and used to retrieve similar text from the Web. The keyword meta information embedded in those pages for search engines is then ranked
Text keywords at different semantic levels have different semantic representation abilities. Although words have been organized by semantic dictionaries (e.g. WordNet) with exact semantics, the dictionaries can not be constructed automatically by machine and there are still many words which are not included in the
Traditional text learning algorithms need labeled documents to supervise the learning process, but labeling documents of a specific class is often expensive and time consuming. We observe it is convenient to use some keywords(i.e. class-descriptions) to describe class sometimes. However, short class-description
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.