Using real-time online preprocessed mouse tracking for lower storage and transmission costs

Note

The original article was granted open access licensed under creative commons (CC-BY) where you are free to copy, reuse, modify, distribute, commercial, etc, but required to give full citation:

1. Authors are Fajar Purnama (me) and Tsuyoshi Usagawa.
2. Title of the article is Using real-time online preprocessed mouse tracking for lower storage and transmission costs.
3. Published in Journal of Big Data, Volume 7, Number 27, Page 1–22, 10 April 2020, DOI is 10.1186/s40537–020–00304-x.
4. Available at https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00304-x.

Althought it is already fully available online, I would like to rewrite it in .html and share to as many platform as possible. Who knows if the original site goes down? Also, I have a circumstance to read it all over again and why not rewrite it at the same time to make it more fun. Eventhough the original is licensed CC-BY but the rewritten version I will license as customized CC-BY-SA where you are also allowed to sell my contents but with a condition that you must mention that the free and open version is available here. In summary, the mention must contain the keyword “free” and “open” and the location such as the link to this content.

Abstract

Pageview is the most popular webpage analytic metric in all sectors including blogs, business, e-commerce, education, entertainment, research, social media, and technology. To perform deeper analysis, additional methods are required such as mouse tracking, which can help researchers understand online user behavior on a single webpage. However, the geometrical data generated by mouse tracking are extremely large, and qualify as big data. A single swipe on a webpage from left to right can generate a megabyte (MB) of data. Fortunately, the geometrical data of each x and y point of the mouse trail are not always needed. Sometimes, analysts only need the heat map of a certain area or perhaps just a summary of the number of activities that occurred on a webpage. Therefore, recording all geometrical data is sometimes unnecessary. This work introduces preprocessing during real-time and online mouse tracking sessions. The preprocessing that is introduced converts the geometrical data from each x and y point to a region-of-interest concentration, in…