Read e-book online Analyzing and Influencing Search Engine Results: Business PDF

By Sönke Lieberam-Schmidt

ISBN-10: 3834924539

ISBN-13: 9783834924537

ISBN-10: 3834989150

ISBN-13: 9783834989154

The consistent progress of the realm huge internet (WWW) creates a requirement for brand spanking new innovations which are precious for net searchers in addition to for info providers. whereas correct and dependent effects turned tougher to discover by way of se's, the significance for companies to be discovered on seen positions of the WWW has immensely elevated. Sönke Lieberam-Schmidt analyzes the influence that search engine marketing (SEO) has at the monetary pursuits of net companies. He buildings to be had web optimization ability, integrates them in an internet site construction technique confirmed to achieve success in perform, and develops types for choosing the proper key phrases. For se's, he offers new tools of grouping and providing results.

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The number and type of the utility indexes depend on the features of the query engine. g. related-page finders or a site index that stores the domain name with pages belonging to this domain. Some features like PageRank calculations are performed in a later phase by the analyzer module. The indexer also builds an URL repository to resolve the URL of a document. 3 Analyzer Based on the databases created by the indexer, the analyzer performs several preliminary calculations for different purposes concerning the search, depending on the purpose and functionality of the search engine.

Because log files can consist of many and large files, it can be necessary to process them in a parallelized way. 2 shows the map and the reduce function adapted for this task. 9: Map and reduce step for log file analysis example The first step is performed by the map function processing the log files. It analyzes the log files and produces a tuple k2 , v2 = u, 1 for each URL it finds in the log files. These tuples form the list(k2 , v2 ). 9 shows the intermediate output. This map function can now be processed in parallel on different machines.

Inspired by the map and reduce functionality of L ISP and other functional languages, MapReduce prevents the developer from the need to explicitly consider these issues by himself. 7). The challenge is to find an appropriate partition. 8: MapReduce sample input for log file analysis parallel must not alter the solution. The output data can be wrong in the case of neglecting crucial dependencies between the tasks. In order to use a standard framework that can be applied to different problems, the input and output data have to exist in a standard structure.

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Analyzing and Influencing Search Engine Results: Business and Technology Impacts on Web Information Retrieval by Sönke Lieberam-Schmidt

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