Search Engine Optimization Process: A Concurrent Intelligent Computing Approach

The modification of customers' behaviors, the competition and the increase in the number of websites have forced companies to improve their visibility on the Internet. Search engines are widely used by customers and companies have to be present in the search engines results pages to be able to reach their clients. Different techniques have been developed to optimize the website's ranking on search engines, such as the SEO (Search Engine Optimization). The search engine optimization is the process of improving a website's position in the Internet search engine results. But the search engines protect their ranking models and results are long and difficult to obtain. Thus the non-transparency of ranking models, the important number of interactions, and the uncertainty in terms of results make the SEO process a complex problem. In order to permit its adaptability and sustainability in a dynamic and uncertain environment, the SEO process needs the elaboration of holistic and concurrent engineering approaches. In this paper, we used the multi-agent paradigm which is appropriate to solve concurrent and distributed problems. By decomposing the SEO process in sub-entities represented by communities of autonomous agents such as requirements, functions, constraints and solutions, we were able to analyze interactions and actions that take place into this process. A multi-agent based simulation using data from pharmacy websites was developed to test our approach.