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Due to the explosive growth of the amount of Web information, the effectiveness of keyword-based searching methods appears to reach a limit. One major reason is that the mixture of content and presentation information hinders machines in understanding the context of Web information and as a result, the performance of
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.
extends the VSM based on keyword, it consider that the keywords in the page have different weight in the different position;Integrating the principles of Page-Rank, link analysis also considers that anchor text and website of the web page relevant with the theme.
The World Wide Web is growing at a rate of about a million pages per day, making it tougher for search engines to extract relevant information for its users. Earlier Search Engines used simple indexing techniques to search for keywords in websites and gave more weightage to pages with higher frequency of keyword
being browsed, to discover relevant keywords for each document, and to effectively cluster the documents into semantically-significant groupings. The quality of the links is improved over time through passive user feedback collection. Our system can be deployed as a web service and has been tested on offline datasets as
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.