Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility
It has been claimed that human mobility is highly predictable and an upper bound of 93% predictability is achievable. However, there is a significant gap between the upper bound of predictability and the actual prediction accuracy in many data sets. This paper points out that this gap is caused by t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9142211/ |
| _version_ | 1818853284592484352 |
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| author | Junyao Guo Sihai Zhang Jinkang Zhu Rui Ni |
| author_facet | Junyao Guo Sihai Zhang Jinkang Zhu Rui Ni |
| author_sort | Junyao Guo |
| collection | DOAJ |
| description | It has been claimed that human mobility is highly predictable and an upper bound of 93% predictability is achievable. However, there is a significant gap between the upper bound of predictability and the actual prediction accuracy in many data sets. This paper points out that this gap is caused by the difference between the user's actual distribution and the hypothesis in the derivation through the analysis on the upper bound of predictability. Then two statistics of the target user's mobility traces are proposed to measure this gap, whose effectiveness is validated by simulated traces and real-world data sets using five prevailing prediction models. The proposed MLP statistics can help with assessing the data quality and designing prediction algorithms. Our work makes the predictability upper bound become a more effective measure and extends the understanding of predictability research in human mobility prediction. |
| first_indexed | 2024-12-19T07:34:22Z |
| format | Article |
| id | doaj.art-35c241cb255e414fba5bd9cac716b28b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:34:22Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-35c241cb255e414fba5bd9cac716b28b2022-12-21T20:30:36ZengIEEEIEEE Access2169-35362020-01-01813185913186910.1109/ACCESS.2020.30098689142211Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human MobilityJunyao Guo0https://orcid.org/0000-0002-0967-1762Sihai Zhang1https://orcid.org/0000-0001-5758-2169Jinkang Zhu2https://orcid.org/0000-0001-9177-0315Rui Ni3https://orcid.org/0000-0002-4382-7580Key Laboratory of Wireless-Optical Communications, University of Science and Technology of China, Hefei, ChinaKey Laboratory of Wireless-Optical Communications, University of Science and Technology of China, Hefei, ChinaPCNSS, University of Science and Technology of China, Hefei, ChinaWireless Technology Laboratory, 2012 Laboratory, Huawei Technologies Company Ltd., Shenzhen, ChinaIt has been claimed that human mobility is highly predictable and an upper bound of 93% predictability is achievable. However, there is a significant gap between the upper bound of predictability and the actual prediction accuracy in many data sets. This paper points out that this gap is caused by the difference between the user's actual distribution and the hypothesis in the derivation through the analysis on the upper bound of predictability. Then two statistics of the target user's mobility traces are proposed to measure this gap, whose effectiveness is validated by simulated traces and real-world data sets using five prevailing prediction models. The proposed MLP statistics can help with assessing the data quality and designing prediction algorithms. Our work makes the predictability upper bound become a more effective measure and extends the understanding of predictability research in human mobility prediction.https://ieeexplore.ieee.org/document/9142211/Human mobility predictabilityreal entropyCall Detail Records |
| spellingShingle | Junyao Guo Sihai Zhang Jinkang Zhu Rui Ni Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility IEEE Access Human mobility predictability real entropy Call Detail Records |
| title | Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility |
| title_full | Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility |
| title_fullStr | Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility |
| title_full_unstemmed | Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility |
| title_short | Measuring the Gap Between the Maximum Predictability and Prediction Accuracy of Human Mobility |
| title_sort | measuring the gap between the maximum predictability and prediction accuracy of human mobility |
| topic | Human mobility predictability real entropy Call Detail Records |
| url | https://ieeexplore.ieee.org/document/9142211/ |
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