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.
Language Model (LM) constitutes one of the key components in Keyword Spotting (KWS). The rapid development of the World Wide Web (WWW) makes it an extremely large and valuable data source for LM training, but it is not optimal to use the raw transcripts from WWW due to the mismatch of content between the web corpus
system called "WebAngels filter" which uses textual and structural content-based analysis. These analysis are based on a violent keyword dictionary. We focus our attention on the keyword dictionary preparation, and we demonstrate that a semi-automatic keyword dictionary can be used to improve the filtering efficiency of
In this work, we compare various text-based pornographic Web filtering techniques. The techniques include blacklist and keyword blocking. The technique called SV is modified to extract a representative feature vector. Each test Web pagepsilas feature is extracted and gathered as a vector. The vector is then summarized
important words or phrases in the text to other pages, thereby letting users quickly access additional information. An automatic text-annotation system combines keyword extraction and word-sense disambiguation to identify relevant links to Wikipedia pages.
performance. Apart from estimating the best path to follow, our system also expands its initial keywords by using genetic algorithm during the crawling process. To crawl Vietnamese web pages, we apply a hybrid word segmentation approach which consists of combining automata and part of speech tagging techniques for the Vietnamese
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.