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keyword driven crawling with relevancy decision mechanism and uses Ontology concepts which ensures the best path for improving crawler's performance. This paper introduces extraction of URLs based on keyword or search criteria. It extracts URLs for web pages which contains searched keyword in their content and considers such
, sponsored links, headers, footers etc. Hence guiding on to fetch particular documents over the Internet is well supported by search engines, on giving appropriate keywords in form of queries, or either by catalogues generation, which organize documents into hierarchical file structure. But maintenance of such catalogues
these sites. Current techniques simply filter on the basis of URLs blocking and keyword matching or either rely on a large database of pre-classified web addresses. The problem is how to intelligently filter the negative contents, rather than filtering entire websites using their URLs or applying simple keyword matching
With the exponential rise in the amount of information in the World Wide Web, there is a need for a much efficient algorithm for Web Search. The traditional keyword matching as well as the standard statistical techniques is insufficient as the Web Pages they recommend are not highly relevant to the query. With the
keywords. These Web pages are ranked by a newly introduced equation. It is evident that all matched Web pages are not selected by this keyword selection procedure. Hence, unmatched Web pages are checked and named as ‘Secondary’ Web pages. These Web pages are ranked by another new equation. Ranking procedure of
of online advertisement: sponsored search and contextual display advertisement. This paper dedicated on contextual display advertisement. Generally, contextual advertisement implementations based on topical or keyword-based relevance approach. This study addresses the mechanism of advanced contextual advertisement based
since performing a keyword search using search engines like Google, Yahoo etc. presents them with a list of publication site where the user need to click through a series of link to reach the journal web site and go through the details of the journals like Impact Factor, SNIP etc. manually. Suppose if a publication web
keyword search. Since the service crawler will periodically make repeated runs to find new service descriptions or to check the status of already crawled services, the framework is of an inherently dynamic nature. Hence, it is critical to keep track of various entities like visited URLs, already added services and
found will be categorized into three groups: Positive link, Negative link and Neutral link. The objective is to identify whether the link is likely pointing into relevant documents or not. In addition, we also utilize keywords related financial domain to recognize a relevant document. Based on our experiments, the value of
keywords, which lack the semantic data. In this paper the semantic based information retrieval methodology is proposed to get data from the web archives in a specific domain by gathering the domain relevant information with web crawler. By utilizing ontology and semantic information matched with a given user's query is used
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