Search Engine Optimization through Web Page Rank Algorithm
Santosh Kumar Ganta, Satya P Kumar Somayajula · 2011
Search engine technology has had to scale dramatically to keep up with the growth of the web. With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Determining the user intent of Web searches is a difficult problem due to the sparse data available concerning the searcher. We qualitatively analyze samples of queries from seven transaction logs from three different Web search engines containing more than five million queries. The following are our research objectives: Isolate characteristics of informational, navigational, and transactional for Web searching queries by identifying characteristics of each query type that will lead to real world classification. Validate the taxonomy by automatically classifying a large set of queries from a Web search engine. This paper we deal with now is semantic web search engines is the layered architecture and we use this with relation based page rank algorithm. I. Introduction The search engine has no infrastructure or matching techniques to give correct or a related information for the query raised. Now the semantic web solves this problem. Each page contains Meta data with notes, meanings, list of words, definitions, vocabulary for the annotations etc. annotations are based on the classes of concepts and relations among them. For an e.g. a query is entered as hotels-hill station, Ooty. The result of the search engine shows several hotels in and around Ooty. The final results are of nothing to do with the selected city. Only two out of seven results satisfy user needs. The list is so ranked that the end user is not furnished with the information that satisfies his or her intention. Of the ten or twelve pages displayed only the first two may be of importance and the other retrieved information must be discarded ones. The user may go through the other pages only if he is interested. But the query he or she has raised would not get the proper result In this paper, we will prove that relations among concepts embedded into semantic annotations can be effectively exploited to define a ranking strategy for Semantic Web search engines. This sort of ranking behaves at an inner level (that is, it exploits more precise information that can be made available within a Web page) and can be used in conjunction with other established ranking strategies to further improve the accuracy of query results. With respect to other ranking strategies for the Semantic Web, our approach only relies on the knowledge of the user query, the Web pages to be ranked, and the underlying ontology. Thus, it allows us to effectively manage the search space and to reduce the complexity associated with the ranking task. We provide an overview of existing strategies for Semantic Web search, the basic idea behind the proposed approach is presented by resorting to practical examples, formal methodology for deriving the general rule is illustrated and concerning the implementation is provided. An analysis of the algorithm complexity is given, and Experimental results are discussed.