ON-LINE USER TYPE IDENTIFICATION METHOD AND SYSTEM BASED ON VISUAL BEHAVIOUR

摘要

Disclosed are an on-line user type identification method and system based on visual behaviour. Eye movement data of one or more different types of users is collected and processed, a watching information data set and a user type set are obtained, one or more pieces of eye movement feature data are obtained according to watching information in the watching information data set so as to form a sampling data set, the eye movement feature data is selected from the sampling data set to be input into a support vector machine, a user type classifier is obtained by training, a machine learning process is completed so as to obtain a classifier, collected eye movement data of a random on-line user is input into the trained user type classifier, and a user type of the random on-line user is identified according to the classifier. Three types of eye movement feature data when each user browses a web page are acquired and calculated by mainly utilizing eye movement tracking technology, and the types of on-line users are judged according to differences in the eye movement feature data. By means of user identification based on visual behaviour, the eye movement data of the on-line users can be actively recorded, the data can be extracted simply and reliably, and accuracy and reliability are high.