Study on Method of Semantic Extraction Based on Eye Tracking

It is important for recommendation system of E business to predicate consumer's habits by eyes gaze tracking.We explore algorithms to identify people's enjoyment by referencing Find s algorithm，it includes getting the weight of eyes parameters by getting the distance of object examples and negative examples，eyes parameters include the eye gazing time，the pupil size，the blink times and the looking back times.We use SEBET (Semantic Extraction Based Eye Tracking) algorithm to calculate the distance of object examples and negative examples，so we can decide whether consumers enjoy the goods or not from the distance，we extract the emotion semantic from eye tracking successfully.Experiments show the efficiency of our algorithm.