Evaluate a Personalized Multi Agent System through Social Networks: Web Scraping
Amal Trifa, Aroua Hedhili, Wided Lejouad Chaari · 2017
Many new applications have been recently developed to satisfy users special needs on the web. In this context, we are interested in personalized systems and particularly in Personalized Multi-Agent Systems (PMAS) characterized by collective and intelligent resolution in a distributed and parallel environment. This work assesses personalization, the most important characteristic of interface in multi-agent systems. As a few studies dealt with the personalization assessment in a multi-agent system, we try, in this work, to address this issue by focusing on web scraping and crawling social networks. In fact, we propose a new assessment tool that exploits data from user's web navigation in order to improve the delivered personalization, which makes the evaluation process more valuable.