[Objective] This paper aims to improve the performance of search engines optimization through analyzing dynamic informational, navigational and transactional online queries. [Methods] First, the author analyzed user intentions with queries, Web documents and the information needs. Second, for each category of query intention, this paper investigated the changing of Web documents and information needs for different trending queries. [Results] The distribution of popular informational, transactional and navigational queries were different. The informational queries were more dependent on Web documents and needs than the other two types of queries. [Limitations] The data for this study was collected in 29 days. More research is needed to automatically identify and aggregate the popular queries. [Conclusions] Search engines need to list diversified results for informational queries. They need to keep the relevant pages on the first page for navigational queries, maintain the original ranking of relevant pages for the user behavior-related queries, and improve the novelty of results for the entertainment-related queries.
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