User intention mining: A non-intrusive approach to track user activities for web application

Abstract

Monitoring user interaction with web applications is of vital importance as it helps in finding the user’s cognitive behavior towards applications and also helps in analyzing various web metrics. Understanding activity data and finding user insights is next challenge to the web world. User intention can be understood if the user activity logs are associated appropriately with application context. In current scenario, web applications are using crawlers, scrappers, bugs, bots etc. to track user activities and extract out relevant information. Thus, by modifying the source code, it is easy to track and maintain the logs of user activities. But, many organization use third party web applications, where changing the source code is out of reach, making it trickier to maintain the logs of user activities. In this paper, we present an innovative way of logging, processing and extracting out meaningful information by tracking user’s activities on web application.