Table 1.
Summary of notations.
Fig 1.
Examples of maximum predictability calculations, and there are three locations, including D1, D2, and D3.
(a): Co-occurrence matrix of Individual A. Individual A made single trips for D1 to D3, D2 to D3, and D3 to D3. And Individual A took two trips from D1 to D1 and D2 to D2 and six round trips between D1 and D2. (b): Co-occurrence matrix of Individual B. Individual B’s visits are mostly identical to those of Individual A, with the exception that the frequencies for trips from D1 to D3 and D2 to D3 are both zero.
Fig 2.
Examples of non-repeating trips.
(a): Example 1. Under sub-conditional knowledge C3, the trips to D2 and D3 are both 1, which belong to non-repeating trips, and under sub-conditional knowledge C1 and C2, the trips to D1 are 7 and 5, respectively. (b): Trips to D2 and D3 are 1 and 2 under sub-conditional knowledge C3, respectively. These values are mostly lower than those recorded under sub-conditional knowledge C1 and C2.
Table 2.
Statistics of the real-world datasets.
Table 3.
Performance of location prediction models on the real-world datasets.
Table 4.
Performance of different maximum predictabilities on simulation dataset.
Fig 3.
Predictability based on simulation dataset.
(a): Predictability based on Markovian location sequences. (b): Predictability based on Markovian time-location sequences.
Table 5.
Correlation between the maximum prediction accuracy and predictability on real-world datasets.
Fig 4.
Correlation between the maximum accuracy and refined maximum predictability on real-world datasets.
Table 6.
The prediction speeds of different methods on NYC dataset.
Fig 5.
Distribution of the refined maximum predictability on real-world datasets.
Fig 6.
Distributions of the refined maximum predictability and prediction accuracy for different knowledge preference groups.
Table 7.
Performance of the location prediction models.
Fig 7.
Correlations between the maximum accuracy and predictability for different values.
Table 8.
Correlations between the maximum accuracy and predictability when considering different types of knowledge on real-world datasets.