# Process Mining IPTV Customer Eye Gaze Movement Using Discrete-Time Markov Chains +
## 2 Related Work
### Eye Tracking in Research  
Eye tracking has evolved over many years in terms of both its technology and its applications. In 1980, [PERSON] and [PERSON] [18] first brought up the concept of the \"eye-mind hypothesis,\" which was related to studies on reading comprehension. Their work was based on the assumption that \"the eye remains fixated on a word as long as the word is being processed,\" which indicates the strong correlation between what a person is looking at and cognitive processes [11]. The first application of eye-tracking technology was to assist severely disabled people with daily activities by designing an eye-wink interface in the 1990s [19]. Since then, eye tracking has been utilised in a variety of fields of research and commercial applications. For example, one study [12] employs Tobii X60 (a model of eye tracker) to assess how students learn from multimedia sources. In the experiment, there are two groups of students from the second and sixth grades of Primary Education, and they are presented with four different sets of multimedia presentations that include verbal content. Their eye movements are recorded by the eye tracker and measured by the pre-defined metric named \"learning efficiency.\" As a result, they validate the hypothesis that different formats of materials (e.g., text only, image with text, image with audio) work differently for the two age groups. Similarly, the research [15] on the difference between English as a foreign language (EFL) beginners and intermediate-level readers when they read narratives comprised of text and images also applies eye-tracking technology to the analysis of eye movement on the target areas of interest (AOTs). In the same area, to help assess school-aged children's virtual attention and identify potential risks of learning or attention problems, the authors [20] propose an integrated platform consisting of a GP3 eye tracker and the OGAMA application, etc. The platform shows some great potential for future applications in education, VR, or AR development. The same eye tracker and software set were employed in another study in the education area [21]. The authors set up an experiment by recording volunteers' eye gaze moments while they are doing code debugging in front of the computer screen. The study comes up with some algorithms to calculate the efficiency of debugging between two groups of participants. The characteristic parameters are taken into account when dividing participants, and the results show a significant difference between the two groups in terms of efficiency and the number of fixations. It reveals a more efficient way of doing software development. Also, the study has set a successful example for measuring people's perception abilities in the field of education. Eye-tracking technology has also played an important role in the research area of e-commerce. For example, ref. [22] has proposed a framework for evaluating the performance of an e-commerce website in terms of item recommendation. They introduce a neural network at the heart of the framework that is trained with synthetic data regarding the user's demographics and other characteristics. And a GP3 eye tracker is the main piece of equipment in the study to provide gaze movement data on the website with both a vertical and horizontal layout. The results of the study have demonstrated the high prediction accuracy of items being added to baskets and also provided a solid solution to automating an optimal recommendation interface adjustment for an e-commerce website. Additionally, ref. [13] has proposed a new method of evaluating webpage usability by the analysis of eye movement. Eye movements are recorded using a head-mounted eye tracker when participants are instructed to look at four webpages twice per page and locate relevant information.