Ineffectiveness of Dictionary Coding to Infer Predictability Limits of Human Mobility
This work addresses a methodological issue for researchers in human mobility prediction, highlighting an incremental limitation in existing approaches.
The study demonstrated that dictionary coding algorithms are ineffective for inferring predictability limits of human mobility due to their slow convergence, despite being theoretically optimal, as shown through analysis of human movements in urban spaces.
Recently, a series of models have been proposed to predict future movements of people. Meanwhile, dictionary coding algorithms are used to estimate the predictability limit of human mobility. Although dictionary coding is optimal, it takes long time to converge. Consequently, it is ineffective to infer predictability through dictionary coding algorithms. In this report, we illustrate this ineffectiveness on the basis of human movements in urban space.