A Web Mining and Optimization Approach for Improving Data Retrieval Performance in Web Search Engine Outcomes
The web is a collection of documents (information, photographs, audios, videos, and so on) uploaded and published by a huge number of individuals, and at the same time, a great number of people are using online search engines to find their relevant documents. When users use various search engines to do searches, they will receive a vast number of relevant and irrelevant sites in answer to their queries. People are obtaining more irrelevant sites against the query supplied by users, thus new approaches are used to the search results to aid users in navigating the result list. To sort the results to be shown to users, search engines utilise several methods of query optimization and query categorization. As a result, optimal data retrieval is the process of selecting the most relevant information resources from a large collection of data resources. As a result, a method to optimising and integrating online content, web mining, and approaches for boosting a search service's knowledge of user search queries is presented in this work. The focus of the research will be on improving the performance of relevant data retrieval in web search engine results.