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2018 | OriginalPaper | Buchkapitel

Similarity of Mobile Users Based on Sparse Location History

verfasst von : Pasi Fränti, Radu Mariescu-Istodor, Karol Waga

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

We propose a method to measure similarity of users based on their sparse location history such as geo-tagged photos or check-in activity of user. The method is useful when complete movement trajectories are not available. We map each activity point into the nearest location in a predefined set of fixed places. The problem is then formulated as histogram comparison. We compare the performance of similarity measures such as L₁, L₂, L_∞, ChiSquared, Bhattacharyya and Kullback and Leibler divergence using both crisp and fuzzy histograms. Results show that user can be recognized with fair accuracy, and that all similarity measures are suitable except L₂ and L_∞, which perform poorly.

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Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRef

Bao, J., Zheng, Y.H., Mokbel, M.F.: Location-based and preference-aware recommendation using sparse geo-social networking data. In: International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Redondo Beach, CA, pp. 199–208 (2013)

Bezdek, J.C., Ehrlich, R., Full, W.: FCM: the fuzzy c-means clustering algorithm. Comput. Geosci. 10(2–3), 191–203 (1984)CrossRef

Biagioni, J., Krumm, J.: Days of our lives: assessing day similarity from location traces. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds.) UMAP 2013. LNCS, vol. 7899, pp. 89–101. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38844-6_8CrossRef

Cha, S.-H.: Comprehensive survey on distance/similarity measures between probability density functions. Int. J. Math. Models Methods Appl. Sci. 4(1), 300–307 (2007)

Cha, S.-H.: Taxonomy of nominal type histogram distance measures. In: American Conference on Applied Mathematics, Harvard, MA, USA, pp. 325–330 (2008)

Cha, S.-H., Srihari, S.N.: On measuring the distance between histograms. Pattern Recogn. 29(13), 1768–1774 (2008)CrossRef

Chen, X., Pang, J., Xue, R.: Constructing and comparing user mobility profiles for location-based services. In: ACM Symposium on Applied Computing, pp. 261–266 (2013)

De Pessemier, T., Minnaert, J., Vanhecke, K., Dooms, S., Martens, L.: Social recommendations for events. In: ACM Conference on Recommender Systems, Hong Kong, China (2013)

10.

Fober, T., Hullermeier, E.: Similarity measures for protein structures based on fuzzy histogram comparison. In: IEEE International Conference on Fuzzy Systems, Barcelona, pp. 1–7 (2010)

11.

Fränti, P., Waga, K., Khurana, C.: Can social network be used for location-aware recommendation? In: International Conference on Web Information Systems & Technologies (WEBIST 2015), Lisbon, Portugal (2015)

12.

Guy, I., Jacovi, M., Perer, A., Ronen, I., Uziel, E.: Same places, same things, same people?: Mining user similarity on social media. In: ACM Conference on Computer Supported Cooperative Work, Savannah, GA, USA, pp. 41–50 (2010)

13.

Li, X., Guo, L., Zhao, Y.: Tag-based social interest discovery. In: Conference on World Wide Web, Beijing, China, pp. 675–684 (2008a)

14.

Li, Q., Zheng, Y., Xie, X., Chen, Y., Liu, W., Ma, W.-Y.: Mining user similarity based on location history. In: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Paper #34, Irvine, CA, USA (2008b)

15.

Liu, H., Schneider, M.: Similarity measurement of moving object trajectories. In: International Workshop on GeoStreaming, pp. 19–22 (2012)

16.

Mariescu-Istodor, R., Fränti, P.: Grid-based method for GPS route analysis for retrieval. ACM Trans. Spat. Algorithms Syst. 3(3), 8:1–8:28 (2017)

17.

Rubner, Y., Tomasi, C., Guibas, L.J.: A metric for distributions with applications to image databases. In: IEEE International Conference Computer Vision, pp. 59–66 (1992)

18.

Strelkov, V.V.: A new similarity measure for histogram comparison and its application in time series analysis. Pattern Recogn. Lett. 29(13), 1768–1774 (2008)CrossRef

19.

Waga, K., Tabarcea, A., Fränti, P.: Recommendation of points of interest from user generated data collection. In: IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), Pittsburgh, USA (2012)

20.

Wang, H., Liu, K.: User oriented trajectory similarity search. In: International Workshop on Urban Computing, pp. 103–110 (2012)

21.

Yang, X., Steck, H., Guo, Y., Liu, Y.: On Top-k recommendation using social networks. In: ACM Conference on Recommender Systems, Dublin, Ireland, pp. 67–74 (2012)

22.

Ying, J.J.C., Lu, E.H.C., Lee, W.C., Wen, T.C.M., Tseng, V.S.: Mining user similarity from semantic trajectories. In: International Workshop on Location Based Social Networks, San Jose, CA, USA (2010)

23.

Zheng, V.W., Zheng, Y., Xie, X., Yang, Q.: Collaborative location and activity recommendations with GPS history data. In: ACM International Conference on World Wide Web, Raleigh, NC, USA, pp. 1029–1038 (2010)

Titel: Similarity of Mobile Users Based on Sparse Location History
verfasst von: Pasi Fränti
Radu Mariescu-Istodor
Karol Waga
Verlag: Springer International Publishing
Buch: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-91252-3

Electronic ISBN: 978-3-319-91253-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-91253-0_55

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