By Weiyi Meng, Clement Yu, M. Tamer Ozsu
One of the seek instruments at the moment on the net, se's are the main popular because of the recognition of significant se's corresponding to Google and Yahoo!. whereas tremendous winning, those significant se's do have critical obstacles. This ebook introduces large-scale metasearch engine know-how, which has the capability to beat the constraints of the search engines. basically, a metasearch engine is a seek method that helps unified entry to a number of present se's via passing the queries it gets to its part se's and aggregating the lower back effects right into a unmarried ranked checklist. A large-scale metasearch engine has hundreds of thousands or extra part se's. whereas metasearch engines have been at the start prompted through their skill to mix the hunt assurance of a number of se's, there also are different advantages comparable to the aptitude to acquire greater and brisker effects and to arrive the Deep internet. the next significant elements of large-scale metasearch engines could be mentioned intimately during this ebook: seek engine choice, seek engine incorporation, and end result merging. hugely scalable and automatic suggestions for those elements are emphasised. The authors make a powerful case for the viability of the large-scale metasearch engine expertise as a aggressive expertise for internet seek. desk of Contents: creation / Metasearch Engine structure / seek Engine choice / seek Engine Incorporation / consequence Merging / precis and destiny examine
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Additional info for Advanced Metasearch Engine Technology
Result extractor) is needed to extract the correct SRRs from each response page so that the SRRs from different component search engines can be merged into a single ranked list. This program is sometimes called an extraction wrapper. Since different search engines often format their results differently, a separate result extractor is usually needed for each component search engine. 1. 2: A Portion of a Response Page from Google. manually, for large-scale metasearch engines, it is desirable to develop techniques that can generate the extractors automatically.
Typically, when a Web page is modified, those search engines that indexed the Web page will not be notified of the modification. Before a search engine can re-fetch and re-index a modified Web page, the representation of the Web page in the search engine is based on a stale or out-dated version of the page. Due to the huge size of the Web, Web crawlers of large search engines can only afford to revisit their previously indexed pages periodically (from days to weeks). As a result, between two visits by a search engine’s crawler, a page may experience multiple changes.
2) The result merging component of the metasearch engine can produce better results by taking advantage of the fact that the document collections of major search engines have significant overlaps. This means that many shared documents have the chance to be ranked by different search engines for any given query. If the same document is retrieved by multiple search engines, then the likelihood that the document is relevant to the query increases significantly because there is more evidence to support its relevance.