# Process Mining IPTV Customer Eye Gaze Movement Using Discrete-Time Markov Chains +
## 6 Conclusions  
Our study in this paper has provided some interesting insights into the eye fixation data from users of the BT Player app by applying machine learning and process mining technology (Markov Model). The aim of the research was to better understand how participants interacted with the app, with the ultimate goal of using these results to improve the product design in a way that will increase the sales of TV shows or films on BT Player. Also, the results have proved that the methodology of DTMC modelling and statistical analysis fits in well with industrial scenarios and requirements. Some of these insights can demonstrate that a product design is either working, in which case it should remain the same going forward, or that there are some elements that could be improved. Such information was revealed by DTMC transition matrices as well as \"steady states distribution,\" etc. Moreover, observing the trajectory of eye fixations over a period of time has also provided some interesting results in terms of human behaviour when viewing screens. There is evidence to corroborate the fact that we read on screens from left to right, as we would expect due to this being the same direction that we read and write ordinarily. We also read in the \"F\" shape, in straight lines horizontally and vertically rather than diagonally. The \"most likely trajectory\" on the screen was also a significant finding in our study as a summary of the possible path of eye gaze movement. Additionally, the information in relation to the expected time (mean passage time) to different screens and AOIs can be interpreted as the level of importance among different on-screen parts for viewers. We plan to introduce more variables into the current methodology of the paper as part of our future study. For instance, the fixation duration on each AOI was not used in the paper. In that case, a continuous-time Markov chain could be applied. Also, there are some limitations to our study, one of which is that we didn't do much quantitative analysis of the eye tracker data, and that can lead to partially missing information in the human-computer interaction. Then, in addition to eye tracking technology, another method of monitoring IPTV viewer interaction should be used, such as click events on the remote control, which will provide a comparison between two parallel actions and generate a more comprehensive model. The workflow described in this paper and its Java software implementation were re-used in a second eye-tracking study at BT, which addressed a different set of IPTV user scenarios. As such, it is believed that the methodology in this study can be a good foundation for further development and can be applied to other HCI research, e.g., usability evaluation, where an eye tracker is possibly in use. It is also generally applicable to data that comes in the format of sequential events, and such data can come from various devices like TVs, smartphones, tablets, IoT sensors, etc., and different domains. It also allows for the measurement and summarization of cognitive processes when people interact with screens. **Author Contributions:** Conceptualization, Z.C., S.Z., S.M. and I.K. ; methodology, Z.C., S.Z., S.M., M.M. and I.K. ; software, Z.C., M.M. and F.H. ; validation, Z.C., S.Z., S.M., F.H. and B.A. ; formal analysis, Z.C. and F.H. ; investigation, Z.C. and F.H. ; resources, Z.C., M.M. and I.K. ; data curation, Z.C. and M.M.M. ; writing--original draft preparation, Z.C. and F.H. ; writing--review and editing, S.Z., S.M., M.M., B.A. and I.K. ; visualization, Z.C. and F.H. ; supervision, S.Z. and S.M. ; project administration, S.Z., S.M. and I.K. ; funding acquisition, S.Z. and S.M. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Data Availability Statement:** Not applicable. **Acknowledgments:** This research is supported by BTIIC (the BT Ireland Innovation Centre), funded by BT and Invest Northern Ireland.