Increasing the accuracy of web suggestion system using fuzzy neural network and bio-algorithms

The growing number of information on the web and the addition of different web pages and websites to this space has made users face problems. These problems appear to users when users are trying to obtain information on a particular topic, and finding all the pages that are suggested to them is a difficult and time consuming process. In the current research, a profile is first created based on the behavioral characteristics of users at different sessions that result from web server logs. These include things like the frequency of user page views, the length of time the user has been on different pages, and the date the page was viewed. We then group them using the clustering method, then fuzzy inference system, extract the fuzzy rules according to the interests of the users and their clusters, and after obtaining the users’ movement patterns, they Insertneural network into vector format Other tools such as bio-algorithms can be useful by obtaining optimal parameters in optimizing predictions and increasing accuracy in fuzzy neural network. The evaluation criteria in this study is accuracy.