Mopsi location-based service

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Abstract

Mopsi is a location-based platform for storing photos and GPS tracks of the users. It allowed user to share their data on-line with real-time user location, communicate with other users, share the data in Facebook, browse the collected photos and tracks on map, perform searches and ask recommendations. Mopsi was operational from 2009 to 2020. This paper documents the history of Mopsi, its main functionalities, research achievements, and the collected data.

Keywords

location-based services / LBS / Mopsi / ubiquitous computing / mobile platform

CHANGE HISTORY

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References

[1] G. Hariharan, P. Fränti, S. Mehta, Data mining for personal navigation, Proceedings of Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, 2002, 355-365. https://doi.org/10.1117/12.460246

[2] A. Tabarcea, N. Gali, P. Fränti, Framework for location-aware search engine, J. Locat. Based Serv., 11 (2017), 50-74. https://doi.org/10.1080/17489725.2017.1407001

[3] E. Cho, S. A. Myers, J. Leskovec, Friendship and mobility: user movement in location-based social networks, Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011, 1082-1090. https://doi.org/10.1145/2020408.2020579

[4] H. Huang, Y. Cheng, W. Dong, G. Gartner, J. M. Krisp, L. Meng, Context modeling and processing in location based services: research challenges and opportunities, J. Locat. Based Serv., 18(2024), 381-407. https://doi.org/10.1080/17489725.2024.2306349

[5] X. Wei, Y. Qian, C. Sun, J. Sun, Y. Liu, A survey of location-based social networks: problems, methods, and future research directions, GeoInformatica, 26 (2022), 159-199. https://doi.org/10.1007/s10707-021-00450-1

[6] H. Katsumi, W. Yamada, K. Ochiai, Characterizing generic POI: a novel approach for discovering tourist attractions, Journal of Information Processing, 31 (2023), 265-277. https://doi.org/10.2197/ipsjjip.31.265

[7] K. Waga, A. Tabarcea, P. Fränti, Context aware recommendation of location-based data, Proceedings of 15th International Conference on System Theory, Control and Computing, 2011, 658-663.

[8] K. Waga, A. Tabarcea, P. Fränti, Recommendation of points of interest from user generated data collection, Proceedings of 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012, 550-555. https://doi.org/10.4108/icst.collaboratecom.2012.250451

[9] P. Fränti, J. Chen, A. Tabarcea, Four aspects of relevance in location-based media: content, time, location and network, Proceedings of the 7th International Conference on Web Information Systems and Technologies, 2011, 413-417.

[10] R. Mariescu-Istodor, P. Fränti, CellNet: inferring road networks from GPS trajectories, ACM Trans. Spat. Algor., 4 (2018), 8. https://doi.org/10.1145/3234692

[11] J. Biagioni, J. Eriksson, Inferring road maps from global positioning system traces: survey and comparative evaluation, Transport. Res. Rec., 2291 (2012), 61-71. https://doi.org/10.3141/2291-08

[12] M. Ahmed, S. Karagiorgou, D. Pfoser, C. Wenk, A comparison and evaluation of map construction algorithms using vehicle tracking data, GeoInformatica, 19 (2015), 601-632. https://doi.org/10.1007/s10707-014-0222-6

[13] M. H. Sharker, H. A. Karimi, J. C. Zgibo, Health-optimal routing in pedestrian navigation services, Proceedings of the First ACM SIGSPATIAL International Workshop on Use of GIS in Public Health, 2012, 1-10. https://doi.org/10.1145/2452516.2452518

[14] M. H. Sharker, H. A. Karimi, Computing least air pollution exposure routes, Int. J. Geogr. Inf. Sci., 28 (2014), 343-362. https://doi.org/10.1080/13658816.2013.841317

[15] P. Fränti, R. Mariescu-Istodor, L. Sengupta, O-Mopsi: mobile orienteering game for sightseeing, exercising and education, ACM Trans. Multim. Comput., 13 (2017), 56. https://doi.org/10.1145/3115935

[16] B. de Moura Morceli, A. Porfirio Dal Poz, Road extraction from low-cost GNSS-device dense trajectories, J. Locat. Based Serv., 17 (2023), 251-270. https://doi.org/10.1080/17489725.2023.2216670

[17] J. Yang, X. Ye, B. Wu, Y. Gu, Z. Wang, D. Xia, et al., DuARE: automatic road extraction with aerial images and trajectory data at Baidu maps, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022, 4321-4331. https://doi.org/10.1145/3534678.3539029

[18] J. Tang, M. Deng, J. Huang, H. Liu, X. Chen, An automatic method for detection and update of additive changes in road network with GPS trajectory data, ISPRS Int. J. Geo-Inf., 8 (2019), 411. https://doi.org/10.3390/ijgi8090411

[19] R. Mariescu-Istodor, P. Fränti, Detecting location-based user actions, Proceedings of the 14th International Conference on Location Based Services, 2018, 1-6. https://doi.org/10.3929/ethz-b-000225579

[20] R. Bakhshandeh, M. Samadi, Z. Azimifar, J. Schaeffer, Degrees of separation in social networks archived, Proceedings of the International Symposium on Combinatorial Search, 2011, 18-23. https://doi.org/10.1609/socs.v2i1.18200

[21] P. Fränti, K. Waga, C. Khurana, Can social network be used for location-aware recommendation? Proceedings of the 11th International Conference on Web Information Systems and Technologies, 2015, 558-565. https://doi.org/10.5220/0005495805580565

[22] M. Fatemi, K. Kucher, M. Laitinen, P. Fränti, Self-similarity of Twitter users, Proceedings of Swedish Workshop on Data Science (SweDS), 2021, 1-7. https://doi.org/10.1109/SweDS53855.2021.9638288

[23] H. Jiang, J. Li, P. Zhao, F. Zeng, Z. Xiao, A. Iyengar, Location privacy-preserving mechanisms in location-based services: a comprehensive survey, ACM Comput. Surv., 54 (2021), 4. https://doi.org/10.1145/3423165

[24] P. Fränti, S. Sieranoja, K. Wikström, T. Laatikainen, Clustering diagnoses from 58M patient visits in Finland between 2015 and 2018, JMIR Med. Inf., 10 (2022), e35422. https://doi.org/10.2196/35422

[25] P. Fränti, R. Mariescu-Istodor, A. Akram, M. Satokangas, E. Reissell, Can we optimize locations of hospitals by minimizing the number of patients at risk? BMC Health Serv. Res., 23 (2023), 415. https://doi.org/10.1186/s12913-023-09375-x

[26] S. Heitmann, A. Pagotto, C. Kray, Approximate vs. precise location in popular location-based services, J. Locat. Based Serv., in press. https://doi.org/10.1080/17489725.2024.2310006

[27] P. Fränti, Mobile navigation for a broad consumer's market: dynamic map handling, GIM Int., 17 (2003), 28-31.

[28] P. Fränti, A. Tabarcea, J. Kuittinen, V. Hautamäki, Location-based search engine for multimedia phones, Proceedings of IEEE International Conference on Multimedia and Expo, 2010, 558-563. https://doi.org/10.1109/ICME.2010.5583538

[29] P. Fränti, J. Kuittinen, A. Tabarcea, L. Sakala, MOPSI location-based search engine: concept, architecture and prototype, Proceedings of the 2010 ACM Symposium on Applied Computing, 2010, 872-873. https://doi.org/10.1145/1774088.1774268

[30] M. Rezaei, P. Fränti, Real-time clustering of large geo-referenced data for visualizing on map, Adv. Electr. Comput. Eng., 18(2018), 63-74. https://doi.org/10.4316/AECE.2018.04008

[31] R. Mariescu-Istodor, P. Fränti, Grid-based method for GPS route analysis for retrieval, ACM Trans. Spat. Algor., 3 (2017), 8. https://doi.org/10.1145/3125634

[32] P. Fränti, R. Mariescu-Istodor, Averaging GPS segment competition 2019, Pattern Recogn., 112 (2021), 107730. https://doi.org/10.1016/j.patcog.2020.107730

[33] K. Waga, A. Tabarcea, R. Mariescu-Istodor, P. Fränti, Real time access to multiple GPS tracks, Proceedings of the 9th International Conference on Web Information Systems and Technologies, 2013, 293-299. https://doi.org/10.5220/0004370102930299

[34] M. Chen, M. Xu, P. Fränti, A fast O(N) multi-resolution polygonal approximation algorithm for GPS trajectory simplification, IEEE Trans. Image Process., 21 (2012), 2770-2785. https://doi.org/10.1109/TIP.2012.2186146

[35] R. Mariescu-Istodor, P. Fränti, Context-aware similarity of GPS trajectories, J. Locat. Based Serv., 14 (2020), 231-251. https://doi.org/10.1080/17489725.2020.1842923

[36] R. Mariescu-Istodor, P. Fränti, Gesture input for GPS route search, In: Structural, syntactic, and statistical pattern recognition, Cham: Springer, 2016, 439-449. https://doi.org/10.1007/978-3-319-49055-7_39

[37] K. Waga, A. Tabarcea, M. Chen, P. Fränti, Detecting movement type by route segmentation and classification, Proceedings of 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012, 1-6. https://doi.org/10.4108/icst.collaboratecom.2012.250450

[38] R. Mariescu-Istodor, A. Tabarcea, R. Saeidi, P. Fränti, Low complexity spatial similarity measure of GPS trajectories, Proceedings of the 10th International Conference on Web Information Systems and Technologies (WEBIST-2014), 2014, 62-69. https://doi.org/10.5220/0004940500620069

[39] R. Mariescu-Istodor, P. Heng, P. Fränti, Roundness measure for GPS routes, Proceedings of the 14th International Conference on Location Based Services, 2018, 81-86. https://doi.org/10.3929/ethz-b-000225594

[40] J. W. Yang, R. Mariescu-Istodor, P. Fränti, Three rapid methods for averaging GPS segments, Appl. Sci., 9 (2019), 4899. https://doi.org/10.3390/app9224899

[41] B. Jimoh, R. Mariescu-Istodor, P. Fränti, Is medoid suitable for averaging GPS trajectories? ISPRS Int. J. Geo-Inf., 11 (2022), 133. https://doi.org/10.3390/ijgi11020133

[42] R. Mariescu-Istodor, P. Fränti, Fast travel distance estimation using overhead graph, J. Locat. Based Serv., 15 (2021), 261-279. https://doi.org/10.1080/17489725.2021.1889058

[43] S. Sieranoja, T. Kinnunen, P. Fränti, GPS trajectory biometrics: from where you were to how you move, In: Structural, syntactic, and statistical pattern recognition, Cham: Springer, 2016, 450-460. https://doi.org/10.1007/978-3-319-49055-7_40

[44] P. Fränti, R. Mariescu-Istodor, K. Waga, Similarity of mobile users based on sparse location history, In: Artificial intelligence and soft computing, Cham: Springer, 2018, 593-603. https://doi.org/10.1007/978-3-319-91253-0_55

[45] R. Mariescu-Istodor, R. Ungureanu, P. Fränti, Real-time destination prediction for mobile users, Adv. Cartogr. GIScience Int. Cartogr. Assoc., 2 (2019), 1-7. https://doi.org/10.5194/ica-adv-2-10-2019

[46] P. Fränti, Mopsi routes: creative ways to analyze GPS tracks, manuscript.

[47] N. Gali, P. Fränti, Content-based title extraction from web page, Proceedings of the 12th International Conference on Web Information Systems and Technologies, 2016, 204-210. https://doi.org/10.5220/0005794102040210

[48] N. Gali, R. Mariescu-Istodor, P. Fränti, Using linguistic features to automatically extract web page title, Expert Syst. Appl., 79 (2017), 296-312. https://doi.org/10.1016/j.eswa.2017.02.045

[49] M. Rezaei, N. Gali, P. Fränti, ClRank: a method for keyword extraction from web pages using clustering and distribution of nouns, Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015, 79-84. https://doi.org/10.1109/WI-IAT.2015.64

[50] H. Shah, P. Fränti, Combining statistical, structural, and linguistic features for keyword extraction from web pages, Appl. Comput. Intell., 2 (2022), 115-132. https://doi.org/10.3934/aci.2022007

[51] N. Gali, A. Tabarcea, P. Fränti, Extracting representative image from web page, Proceedings of the 11th International Conference on Web Information Systems and Technologies, 2015, 411-419. https://doi.org/10.5220/0005438704110419

[52] N. Gali, R. Mariescu-Istodor, P. Fränti, Functional classification of websites, Proceedings of the 8th International Symposium on Information and Communication Technology, 2017, 34-41. https://doi.org/10.1145/3155133.3155178

[53] N. Gali, R. Mariescu-Istodor, P. Fränti, Similarity measures for title matching, Proceedings of 23rd International Conference on Pattern Recognition (ICPR), 2016, 1549-1554. https://doi.org/10.1109/ICPR.2016.7899857

[54] N. Gali, R. Mariescu-Istodor, D. Hostettler, P. Fränti, Framework for syntactic string similarity measures, Expert Syst. Appl., 129 (2019), 169-185. https://doi.org/10.1016/j.eswa.2019.03.048

[55] R. Mariescu-Istodor, A. S. M. Sayem, P. Fränti, Activity event recommendation and attendance prediction, J. Locat. Based Serv., 13 (2019), 293-319. https://doi.org/10.1080/17489725.2019.1660423

[56] P. Fränti, N. Fazal, Design principles for content creation in location-based games, ACM Trans. Multim. Comput., 19 (2023), 165. https://doi.org/10.1145/3583689

[57] N. Fazal, P. Fränti, Social media data for content creation in location-based games, J. Locat. Based Serv., in press. https://doi.org/10.1080/17489725.2024.2414000

[58] N. Fazal, P. Fränti, Relevant tag extraction based on image visual content, In: Applied intelligence, Singapore: Springer, 2024, 283-295. https://doi.org/10.1007/978-981-97-0827-7_25

[59] N. Fazal, R. Mariescu-Istodor, P. Fränti, Using open street map for content creation in location-based games, Proceedings of 29th Conference of Open Innovations Association (FRUCT), 2021, 109-117. https://doi.org/10.23919/FRUCT52173.2021.9435502

[60] N. Fazal, K. Q. Nqyuen, P. Fränti, Efficiency of web crawling for geo-tagged image retrieval, Webology, 16 (2019), 16-39. https://doi.org/10.14704/WEB/V16I1/A177

[61] N. Fazal, P. Fränti, Mopsify: gamified crowdsourcing for content creation in location-based games, Proceedings of the Sixteenth International Conference on Advanced Geographic Information Systems, Applications, and Services, 2024, 18-22.

[62] P. Fränti, L. Kong, Puzzle-Mopsi: a location-puzzle game, Appl. Comput. Intell., 3 (2023), 1-12. https://doi.org/10.3934/aci.2023001

[63] L. Sengupta, R. Mariescu-Istodor, P. Fränti, Planning your route: where to start? Comput. Brain Behav., 1 (2018), 252-265. https://doi.org/10.1007/s42113-018-0018-0