A New Approach for Search Engine Optimization based Case Based Reasoning to detect user's intent

The main objective of the Search Engine Optimization is to understand the user's query / user's intent. Our goal is to provide the optimal result for each user's query in order to adapt the content to user profile. To overcome this challenge involves first, to understanding the search intentions of internet user's and paramount to the search engines and in the second way, to understand the traffic behavior for each user. This can be accomplished by defining the type of content to be produced in order to maximize your chances of positioning yourself, and the use of the traces user's, which include chronology of interactions and productions left by the user during his navigation process. In this paper we present our approach in the field of Search Engine Optimization based on Dynamic Case-Based Reasoning (DCBR). In our approach, we focus on the detection and understanding of the user's intent that motivate a user to search on the web. The analysis of the history of research by the reuse of previous traces those are similar to the current situation in a dynamic way. We propose a new approach able to detect the user's intent through the optimization and the monitoring, comparing and analyzing these traces in order to improve the ranking of a website in organic search results and to increase their visibility and quality.