User Profiling in the Chronobot/Virtual Classroom System

The Chronobot/Virtual Classroom (CVC) system is a novel time knowledge exchange platform where any pair of users can exchange their time and knowledge. User profile that contains user attributes, preferences, and learning patterns serves as a primary basis to identify exchange partners and determine exchange rates. In this paper, we described the methodology to acquire knowledge about users i.e. user profile from their activities. The association between user profile and user behaviors (e.g. online reading, chatting and time/knowledge exchanging) is identified by several feedback indicators extracted from browsing history, chatting session and exchange transaction. A linear learning model is constructed to fuse multiple feedback indicators to infer user preference. The methods utilizing user profile to identify the exchange partners and determine the exchange rate are also described in detail.