By Sönke Lieberam-Schmidt
The consistent development of the area huge internet (WWW) creates a requirement for brand new options which are valuable for web searchers in addition to for info providers. whereas appropriate and dependent effects grew to become more durable to discover by means of se's, the significance for companies to be chanced on on obvious positions of the WWW has immensely elevated. Sönke Lieberam-Schmidt analyzes the effect that search engine optimisation (SEO) has at the fiscal pursuits of internet companies. He constructions on hand web optimization ability, integrates them in an internet site construction method confirmed to achieve success in perform, and develops versions for choosing the perfect key phrases. For se's, he offers new tools of grouping and offering results.
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Additional resources for Analyzing and Influencing Search Engine Results: Business and Technology Impacts on Web Information Retrieval
With an increasing number of webpages in the Internet, the quantity of results has augmented. Thus, the presentation of Web-search results has become the new challenge for search engines. The presenter may get a huge number of results back from the searcher. Because the searcher does not “know” about the user’s information need, he takes all results into account that ﬁt to the search query. Thus, the probability for the expected results to be among the delivered results will be higher. However, the probability for the user to actually ﬁnd the expected results will decrease with a higher quantity of results.
In the ﬁrst step a map operation transforms the input data into an intermediate representation map(k1 , v1 ) → list(k2 , v2 ). In a second step a reduce function recombines the intermediate representation into a ﬁnal output reduce (k2 , list(v2 )) → list(v2 ). The functionality of MapReduce is explained using the following simple example. The task is to determine the access frequency of a URL during the analysis of the log ﬁles of a website. The host computer delivering the pages of a website usually stores the URL of each single request in a log ﬁle.
The optimal download time, calculated as T ∗ , is hard to reach under more realistic constraints. Taking into account the intervals w between two downloads and assuming different maximum of the webpages i, gaps between the downloads may become bandwidth BMAX i necessary. The bandwidth restrictions and the gaps can lead to a schedule where the crawler’s bandwidth is not always fully used. The time span Ti the Web server needs to deliver page i is determined by the ﬁle as size Pi and the maximum bandwidth BMAX i Ti = Pi MAX Bi .
Analyzing and Influencing Search Engine Results: Business and Technology Impacts on Web Information Retrieval by Sönke Lieberam-Schmidt