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2017 | OriginalPaper | Buchkapitel

Applying Artificial Neural Networks on Two-Layer Semantic Trajectories for Predicting the Next Semantic Location

verfasst von : Antonios Karatzoglou, Harun Sentürk, Adrian Jablonski, Michael Beigl

Erschienen in: Artificial Neural Networks and Machine Learning – ICANN 2017

Verlag: Springer International Publishing

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Abstract

Location-awareness and prediction play a steadily increasing role as systems and services become more intelligent. At the same time semantics gain in importance in geolocation application. In this work, we investigate the use of artificial neural networks (ANNs) in the field of semantic location prediction. We evaluate three different ANN types: FFNN, RNN and LSTM on two different data sets on two different semantic levels each. In addition we compare each of them to a Markov model predictor. We show that neural networks perform overall well, with LSTM achieving the highest average score of 76,1%.

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Literatur
1.
Zurück zum Zitat Alvares, L.O., Bogorny, V., Kuijpers, B., Moelans, B., Fern, J.A., Macedo, E., Palma, A.T.: Towards semantic trajectory knowledge discovery. In: Data Mining and Knowledge Discovery (2007) Alvares, L.O., Bogorny, V., Kuijpers, B., Moelans, B., Fern, J.A., Macedo, E., Palma, A.T.: Towards semantic trajectory knowledge discovery. In: Data Mining and Knowledge Discovery (2007)
2.
Zurück zum Zitat Biesterfeld, J., Ennigrou, E., Jobmann, K.: Neural networks for location prediction in mobile networks. In: Proceedings of International Workshop on Applications of Neural Networks to Telecommunications, pp. 207–214 (1997) Biesterfeld, J., Ennigrou, E., Jobmann, K.: Neural networks for location prediction in mobile networks. In: Proceedings of International Workshop on Applications of Neural Networks to Telecommunications, pp. 207–214 (1997)
3.
Zurück zum Zitat Eagle, N., Pentland, A.S.: Reality mining: sensing complex social systems. Pers. Ubiquit. Comput. 10(4), 255–268 (2006)CrossRef Eagle, N., Pentland, A.S.: Reality mining: sensing complex social systems. Pers. Ubiquit. Comput. 10(4), 255–268 (2006)CrossRef
4.
Zurück zum Zitat Etter, V., Kafsi, M., Kazemi, E.: Been there, done that: what your mobility traces reveal about your behavior. In: Proceedings of MDC by Nokia Workshop 10th PerCom (2012) Etter, V., Kafsi, M., Kazemi, E.: Been there, done that: what your mobility traces reveal about your behavior. In: Proceedings of MDC by Nokia Workshop 10th PerCom (2012)
5.
Zurück zum Zitat Song, X., Kanasugi, H., Shibasaki, R.: Deeptransport: prediction and simulation of human mobility and transportation mode at a citywide level. In: Proceedings of 25th International Joint Conference on Artificial Intelligence, pp. 2618–2624 (2016) Song, X., Kanasugi, H., Shibasaki, R.: Deeptransport: prediction and simulation of human mobility and transportation mode at a citywide level. In: Proceedings of 25th International Joint Conference on Artificial Intelligence, pp. 2618–2624 (2016)
6.
Zurück zum Zitat Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data Knowl. Eng. 65(1), 126–146 (2008)CrossRef Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Porto, F., Vangenot, C.: A conceptual view on trajectories. Data Knowl. Eng. 65(1), 126–146 (2008)CrossRef
7.
Zurück zum Zitat Vintan, L., Gellert, A., Petzold, J., Ungerer, T.: Person movement prediction using neural nets. In: 1st Workshop on Modeling and Retrieval of Context, vol. 114, pp. 1–12 (2004) Vintan, L., Gellert, A., Petzold, J., Ungerer, T.: Person movement prediction using neural nets. In: 1st Workshop on Modeling and Retrieval of Context, vol. 114, pp. 1–12 (2004)
8.
Zurück zum Zitat Yan, Z., Chakraborty, D., Parent, C., Spaccapietra, S., Aberer, K.: Semantic trajectories: mobility data computation and annotation. ACM Trans. Intell. Syst. Technol. 4(3), 49:1–49:38 (2013)CrossRef Yan, Z., Chakraborty, D., Parent, C., Spaccapietra, S., Aberer, K.: Semantic trajectories: mobility data computation and annotation. ACM Trans. Intell. Syst. Technol. 4(3), 49:1–49:38 (2013)CrossRef
9.
Zurück zum Zitat Ying, J.J.C., Lee, W.C., Weng, T.C., Tseng, V.S.: Semantic trajectory mining for location prediction. In: Proceedings of 19th ACM SIGSPATIAL, GIS 2011, pp. 34–43 (2011) Ying, J.J.C., Lee, W.C., Weng, T.C., Tseng, V.S.: Semantic trajectory mining for location prediction. In: Proceedings of 19th ACM SIGSPATIAL, GIS 2011, pp. 34–43 (2011)
10.
Zurück zum Zitat Zheng, Y., Zhang, L., Xie, X., Ma, W.Y.: Mining interesting locations and travel sequences from GPS trajectories. In: Proceedings of 18th International Conference on WWW, pp. 791–800 (2009) Zheng, Y., Zhang, L., Xie, X., Ma, W.Y.: Mining interesting locations and travel sequences from GPS trajectories. In: Proceedings of 18th International Conference on WWW, pp. 791–800 (2009)
Metadaten
Titel
Applying Artificial Neural Networks on Two-Layer Semantic Trajectories for Predicting the Next Semantic Location
verfasst von
Antonios Karatzoglou
Harun Sentürk
Adrian Jablonski
Michael Beigl
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-68612-7_27