User-generated social media data tagged with geographic information present messages of dynamic spatiotemporal trajectories. These increasing mobility data provide potential opportunities to enhance the understanding of human mobility behaviors. Several trajectory data mining approaches have been proposed to benefit from these rich datasets, but fail to incorporate aspatial semantics in mining. This study investigates mining frequent moving sequences of geographic entities with transit time from geo-tagged data. Different from previous analysis of geographic feature only trajectories, this work focuses on extracting patterns with rich context semantics. We extend raw geographic trajectories generated from geo-tagged data with rich context semantic annotations, use regions-of-interest as stops to represent interesting places, enrich them with multiple aspatial semantic annotations, and propose a semantic trajectory pattern mining algorithm that returns basic and multidimensional semantic trajectory patterns. Experimental results demonstrate that semantic trajectory patterns from our method present semantically meaningful patterns and display richer semantic knowledge.
About author: Guochen Cai received his Ph.D. degree, in 2017, in information technology from James Cook University, Queensland. His current research areas include trajectory data mining, semantic trajectories, recommender systems, and spatio-temporal data mining.
Guochen Cai, Kyungmi Lee, Ickjai Lee.从地理标记数据中挖掘语义轨迹模式[J] Journal of Computer Science and Technology , 2018,V33(4): 849-862
Guochen Cai, Kyungmi Lee, Ickjai Lee.Mining Semantic Trajectory Patterns from Geo-Tagged Data[J] Journal of Computer Science and Technology, 2018,V33(4): 849-862
 Goodchild M F. Citizens as sensors:The world of volunteered geography. GeoJournal, 2007, 69(4):211-221. Girardin F, Fiore F D, Ratti C, Blat J. Leveraging explic itly disclosed location information to understand tourist dy-namics:A case study. Journal of Location Based Services, 2008, 2(1):41-56. Lee I, Cai G, Lee K. Exploration of geo-tagged photos through data mining approaches. Expert Systems with Applications, 2014, 41(2):397-405. Bermingham L, Lee I. Spatio-temporal sequential pattern mining for tourism sciences. Procedia Computer Science, 2014, 29:379-389. Cai G, Hio C, Bermingham L, Lee K, Lee I. Sequential pattern mining of geo-tagged photos with an arbitrary regionsof-interest detection method. Expert Systems with Applications, 2014, 41(7):3514-3526. Giannotti F, Nanni M, Pinelli F, Pedreschi D. Trajectory pattern mining. In Proc. the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2007, pp.330-339. Ying J C, Lee W C, Weng T C, Tseng V S. Semantic trajectory mining for location prediction. In Proc. the Conference on ACM SIGSPATIAL GIS, Nov. 2011, pp.33-43. Parent C, Spaccapietra S, Renso C, Andrienko G, Andrienko N, Bogorny V, Damiani M L, Gkoulalas-Divanis A, Macedo J, Pelekis N et al. Semantic trajectories modeling and analysis. ACM Computing Surveys (CSUR), 2013, 45(4):Article No.42. Zhang C, Han J, Shou L, Lu J, La Porta T. Splitter:Mining fine-grained sequential patterns in semantic trajectories. Proc. VLDB Endow., May 2014, 7(9):769-780. Giannotti F, Nanni M, Pedreschi D. Efficient mining of temporally annotated sequences. In Proc. the 6th SIAM International Conference on Data Mining, April 2006, pp.348-359. Chen C C, Kuo C H, Peng W C. Mining spatial-temporal semantic trajectory patterns from raw trajectories. In Proc. IEEE International Conference on Data Mining Workshop (ICDMW), November 2015, pp.1019-1024. Chen C C, Chiang M F. Trajectory pattern mining:Exploring semantic and time information. In Proc. Conference on Technologies and Applications of Artificial Intelligence (TAAI), November 2016, pp.130-137. Pei J, Han J, Mortazavi-Asl B, Pinto H, Chen Q, Dayal U, Hsu M. PrefixSpan:Mining sequential patterns by prefixprojected growth. In Proc. the 17th International Conference on Data Engineering, April 2001, pp.215-224. Alvares L O, Bogorny V, Kuijpers B, Macedo J A F, Moelans B, Vaisman A. A model for enriching trajectories with semantic geographical information. In Proc. the 15th Annual ACM International Symposium on Advances in Geographic Information Systems, Nov. 2007. Cai G, Lee K, Lee I. Mining semantic sequential patterns from geo-tagged photos. In Proc. the 49th Hawaii International Conference on System Sciences (HICSS), January 2016, pp.2187-2196. Zheng Y T, Zha Z J, Chua T S. Mining travel patterns from geotagged photos. ACM Trans. Intell. Syst. Technol., 2012, 3(3):56:1-56:18. Cai G, Lee K, Lee I. A framework for mining semanticlevel tourist movement behaviours from geo-tagged photos. In Proc. the 29th Australasian Joint Conference in AI, December 2016, pp.519-524. Majid A, Chen L, Mirza H T, Hussain I, Chen G. A system for mining interesting tourist locations and travel sequences from public geotagged photos. Data and Knowledge Engineering, 2015, 95:66-86. Beyer K, Ramakrishnan R. Bottom-up computation of sparse and iceberg cube. ACM SIGMOD Record, 1999, 28(2):359-370.
Copyright 2010 by Journal of Computer Science and Technology