An information system for comparing partner employment schedules

There are various approaches to describing, comparing and converting data nowadays, but there are challenges that require new methods. This article describes the combination of some cluster comparison approaches for the flexibility of design systems. This approach can reduce the impact of missing data when comparing clusters. This method is used in the system of comparison of partner employment schedules, where there is no constant flow of data from the user and the data itself has big differences. In most cases, this data is incomplete, which complicates the cluster comparison process by simple methods. Combining optimistic comparison and realistic methods, you can change the coefficient of similarity for each individual pair of users (a realistic comparison is used for users with a close data set, and an optimistic comparison is for a different set).

The article also describes the possibility of converting point data over a long period (using time) by gluing a factor. This allows to play a long-lasting event only in a few moments. Also, this conversion allows to work with one element at a specific time in the same way as with a time interval.

Thus, using the described approaches reduces the impact of lack of data from users, as well as conditional specific values can be converted into segments close to reality, which allows the projected system to become more flexible.