Abstract
One of existing challenges in personalization of the web is increasing the efficiency of a web in meeting the users' requirements for the contents they require in an optimal state. All the information associated with the current user behavior following in web and data obtained from pervious users’ interaction in web can provide some necessary keys to recommend presentation of services, productions, and the required information of the users. This study aims at presenting a formal model based on colored Petri nets to identify the present user's interest, which is utilized to recommend the most appropriate pages ahead. In the proposed design, recommendation of the pages is considered with respect to information obtained from pervious users' profile as well as the current session of the present user. This model offers the updated proposed pages to the user by clicking on the web pages. Moreover, an example of web is modeled using CPN Tools. The results of the simulation show that this design improves the precision factor. We explain, through evaluation where the results of this method are more objective and the dynamic recommendations demonstrate that the results of the recommended method improve the precision criterion 15% more than the static method.
Highlights
With extending the web, finding the useful information to meet the information required by users has become difficult
Search engines are responsible for addressing this undeniable need
Studying the user’s behaviors in web is considered as an important tool in web mining domain for discovering knowledge related to users interaction with web
Summary
With extending the web, finding the useful information to meet the information required by users has become difficult. These aspects are the content presented in web, layout of the personal pages, and the general structure of the web Formal models such as Petri net and queuing help us analyze the user's behavior with mathematics. On the other hand, are able to analyze and exhibit the actions and behaviors of the system and they have strong mathematical background to cover the concurrency discussion in systems They can be regarded as a formal model in simulation of web structure and modeling user's behavior in webs. The main drawback of the mentioned recommender systems is that they keep the users' models and change them slowly and they do not consider the fact that various sessions of a user or single sessions of users may express their different interests and purposes To eliminate this defect, in the proposed method, the current session of user are followed step by step and due to the user's selection at each step, the recommended pages are suggested, dynamically. The layout of current research is as follow: in the second section, literature is explained, afterwards, a review of last related research is presented in the third section and the forth section includes a presentation of the proposed method and in fifth section, and evaluation, simulation, and results are discussed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
