Development of a Lossy Online Mouse Tracking Method for Capturing User Interaction with Web Browser Content 3/3

in computers •  4 years ago 

5 Conclusion and Future Work

5.1 Conclusion

The author wrote an online mouse tracking application suitable for public implementation and implemented during a quiz session at the Human Interface and Cyber Communication Laboratory, Kumamoto University on the 3rd of January 2019 between approximately 12:00 and 14:30 Japan standard time. The amount of data generated by mouse tracking was investigated during the implementation and found that the cause of huge data generation is the capturing of geometrical data or coordinates of each event. Aside from existing solutions to reduce data, this thesis also implemented and discussed real-time transmission system in mouse tracking data retrieval helps distribute the network's burden across the time domain. The main novelty of this thesis is the select-able geometrical online mouse tracking method where there are possible cases that not all the geometrical data are required. The method allows summarizing of coordinates into areas or deleting the coordinates if they are not necessary. The results showed great reduction in storage and transmission costs. However, the method is lossy because the process is irreversible. Rich mouse tracking data were obtained and in this thesis a new concept of log dept level was discussed with example analysis that include click visualization and activity heatmap which help in identifying the interaction between the students' and the quiz page.

5.2 Future Work

The real-time transmission is not the best solution. A better method is to upgrade the real-time transmission method by integrating smart transmission method where the client can detect the traffic of the network and determine the optimal time for queuing and transmission. Although the select-able geometrical mouse tracking data method works perfectly, there are still problems with execution. If all of the geometrical data are excluded, the most efficient time to transmit the data is only once which is when the user leaves the page. However, the problem lies with the browser where there is currently no way to force the user to wait before the transmission process finishes, leaving potential problem of data loss. The problem for ROI tracking is that it cannot perform smart area determination and labelling. Normally, they are performed by humans. Therefore, one solution is to develop an artificial intelligence for this matter in the future. Finally, this doctoral thesis is only limited to mouse tracking with one type of activity which is examination. There are a various activities such as passage reading, e-commerce, entertainment, Geo-visualization reading, search engine, social media, etc which are open for future work.

Appendix A Data

A.1 Quiz Areas

**Area** **x1, x2, y1, y2** **Area** **x1, x2, y1, y2**
Header 0, 1920, 0, 64 Quiz8 Question 529, 1900, 2453, 2493
Title 16, 1904, 150, 270 Quiz8 Answers 529, 1900, 2494, 2730
Quiz Navigation 18, 364, 291, 532 Quiz9 Flag 384, 528, 2731, 3242
Navigation 16, 366, 551, 1042 Quiz9 Question 529, 1900, 2731, 2831
Administration 18, 364, 1062, 1693 Quiz9 Answers 529, 1900, 2832, 3242
Quiz1 Flag 384, 528, 291, 570 Quiz10 Flag 384, 528, 3243, 3580
Quiz1 Question 529, 1900, 291, 341 Quiz10 Question 529, 1900, 3243, 3343
Quiz1 Answers 529, 1900, 342, 570 Quiz10 Answers 529, 1900, 3341, 3580
Quiz2 Flag 384, 528, 571, 852 Quiz11 Flag 384, 528, 3581, 3856
Quiz2 Question 529, 1900, 571, 621 Quiz11 Question 529, 1900, 3581, 3631
Quiz2 Answers 529, 1900, 622, 852 Quiz11 Answers 529, 1900, 3632, 3856
Quiz3 Flag 384, 528, 853, 1133 Quiz12 Flag 384, 528, 3857, 4169
Quiz3 Question 529, 1900, 853, 903 Quiz12 Question 529, 1900, 3857, 3907
Quiz3 Answers 529, 1900, 904, 1133 Quiz12 Answers 529, 1900, 3908, 4169
Quiz4 Flag 384, 528, 1134, 1441 Quiz13 Flag 84, 528, 4170, 4746
Quiz4 Question 529, 1900, 1134, 1184 Quiz13 Question 529, 1900, 4170, 4520
Quiz4 Answers 529, 1900, 1185, 1441 Quiz13 Answers 529, 1900, 4521, 4746
Quiz5 Flag 384, 528, 1442, 1748 Quiz14 Flag 384, 528, 4747, 5295
Quiz5 Question 529, 1900, 1442, 1492 Quiz14 Question 529, 1900, 4747, 5097
Quiz5 Answers 529, 1900, 1493, 1748 Quiz14 Answers 529, 1900, 5098, 5295
Quiz6 Flag 384, 528, 1749, 2027 Quiz15 Flag 384, 528, 5296, 5842
Quiz6 Question 529, 1900, 1749, 1799 Quiz15 Question 529, 1900, 5296, 5646
Quiz6 Answers 529, 1900, 1800, 2027 Quiz15 Answers 529, 1900, 5647, 5842
Quiz7 Flag 384, 528, 2028, 2452 Footer 0, 1920, 5939, 6116
Quiz8 Flag 384, 528, 2453, 2730 Blank Areas except listed here

A.2 Full Quiz Page Heatmap

a.1.msvisual.jpg

Figure A.1 Visualization of mouse tracking data. Default mouse tracking data can visualize exact points of location, the left image is click visualization and the middle image is a heatmap based on the duration the mouse cursor stays on each point, while ROI tracking can only visualize defined areas and show flows between areas shown on the right image.

Appendix B Copyrights

Below are the publications reused in this thesis that does not require copyright clearance:

Below are the publications reused in this thesis that requires copyright clearance and obtained:

b.1.ieee-permission-crop.jpg

https://s100.copyright.com/CustomerAdmin/PLF.jsp?ref=d6af378c-4d45-49da-90cf-5ce0e54d2473

Material details:

  • Original author's name: Fajar Purnama, Tsuyoshi Usagawa
  • Document title: Incremental Synchronization Implementation on Survey using Hand Carry Server Raspberry Pi
  • Book or journal title: Technical Report, vol. 117, no. 65, ET2017-4, pp. 21-24, year 2017, month 5.
  • Portion: Figure 5

Permission No.: 20GB0052

IEICE hereby grant permission for the use of the material requested above on condition that their requirements are as follows:

  • Indication of source (e.g., author's name, document title, name of journal, volume/issue/page number, publication date, etc.)
  • Indication of copyright (e.g. "Copyright (c)2016 IEICE")

Reference

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