By Sönke Lieberam-Schmidt
The consistent development of the realm broad internet (WWW) creates a requirement for brand spanking new thoughts which are valuable for net searchers in addition to for info providers. whereas suitable and established effects grew to become more durable to discover through se's, the significance for companies to be came across on noticeable positions of the WWW has immensely elevated. Sönke Lieberam-Schmidt analyzes the impression that website positioning (SEO) has at the fiscal pursuits of internet companies. He constructions on hand web optimization potential, integrates them in an internet site construction technique confirmed to achieve success in perform, and develops versions for choosing the appropriate key phrases. For se's, he offers new equipment of grouping and featuring results.
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Extra info for Analyzing and Influencing Search Engine Results: Business and Technology Impacts on Web Information Retrieval
The crawler collects either as many pages as possible from the Web or the necessary amount of pages to reach his goal. 3. , 2003) S IMPLE -C RAWLER(S0 , D, E) Q ← S0 while Q = 0/ do u ← D EQUEUE(Q) d(u) ← F ETCH(u) S TORE (D, d(u), u) L ← PARSE (d (u)) for each v in L do S TORE (E, (u, v)) if ¬ (v ∈ D ∨ v ∈ Q) then E NQUEUE(Q, v) The crawling process starts with an initial set of URLs S0 , it downloads and stores the corresponding webpages (or parts of them) and follows the containing hyperlinks according to an algorithm which may differ from crawler to crawler.
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. 8). If the computation applied on a pair of key and value (k, v) ﬁts in the following general scheme it can easily be parallelized and its data can be accordingly partitioned. 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 ).
Keywords can be located in the body text of a document as well as in headers, in metatags, in tables, in links or in other HTML format elements of the document. Thus, a document d j is characterized by the content of keywords qi (i = 1, . . , I) and their position in certain format elements el (l = 1, . . , L). 3) j=1 contains a reduced set of information – the keywords and their position in the ˆ format elements of the document. When a query is addressed to the index D, the ranking algorithm generates a set of documents (links) which is ordered by the relevancy of the documents found.