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S2R-tree: a pivot-based indexing structure for semantic-aware spatial keyword search

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Abstract

Semantic-aware spatial keyword search is an important technique for digital map services. However, existing indexing and search methods have limited pruning effect due to the high dimensionality in semantic space, causing query efficiency to be a serious issue. To handle this problem, this paper proposes a novel pivot-based hierarchical indexing structure S2R-tree to integrate spatial and semantic information in a seamless way. Instead of indexing objects in the original semantic space, we carefully design a space mechanism to transform the high dimensional semantic vectors to a low dimensional space, so that more effective pruning effect can be achieved. On top of the S2R-tree, an efficient query processing algorithm is further designed, which not only ensures efficient query processing by a set of theoretical bounds, but also returns accurate results despite of the indexing in the low dimensional space. Furthermore, we conduct extensive experiments to evaluate and compare our proposed and baseline methods.

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References

  1. Andreas J, Klein D (2014) How much do word embeddings encode about syntax? In: ACL, pp 822–827

  2. Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022

    Google Scholar 

  3. Bozkaya T, Özsoyoglu ZM (1997) Distance-based indexing for high-dimensional metric spaces. In: SIGMOD, pp 357–368

  4. Cao X, Cong G, Jensen CS, Ooi BC (2011) Collective spatial keyword querying. In: SIGMOD, pp 373–384

  5. Cao X, Chen L, Cong G, Jensen CS, Qu Q, Skovsgaard A, Wu D, Yiu ML (2012) Spatial keyword querying. In: ER, pp 16–29

  6. Cao X, Chen L, Cong G, Xiao X (2012) Keyword-aware optimal route search. PVLDB 5(11):1136– 1147

    Google Scholar 

  7. Cao X, Chen L, Cong G, Guan J, Phan N, Xiao X (2013) KORS: keyword-aware optimal route search system. In: ICDE, pp 1340–1343

  8. Chen L, Cong G (2015) Diversity-aware top-k publish/subscribe for text stream. In: SIGMOD, pp 347–362

  9. Chen L, Cong G, Cao X (2013) An efficient query indexing mechanism for filtering geo-textual data. In: SIGMOD, pp 749–760

  10. Chen L, Cong G, Jensen CS, Wu D (2013) Spatial keyword query processing: an experimental evaluation, vol 6, pp 217–228

    Article  Google Scholar 

  11. Chen L, Cui Y, Cong G, Cao X (2014) SOPS: a system for efficient processing of spatial-keyword publish/subscribe. PVLDB 7(13):1601–1604

    Google Scholar 

  12. Chen L, Cong G, Cao X, Tan K (2015) Temporal spatial-keyword top-k publish/subscribe. In: ICDE, pp 255–266

  13. Chen L, Lin X, Hu H, Jensen CS, Xu J (2015) Answering why-not questions on spatial keyword top-k queries. In: ICDE, pp 279–290

  14. Chen W, Zhao L, Xu J, Liu G, Zheng K, Zhou X (2015) Trip oriented search on activity trajectory. J Comput Sci Technol 30(4):745–761

    Article  Google Scholar 

  15. Chen J, Xu J, Liu C, Li Z, Liu A, Ding Z (2017) Multi-objective spatial keyword query with semantics. In: DASFAA 2017, pp 34–48

    Chapter  Google Scholar 

  16. Chen Z, Cong G, Zhang Z, Fu TZJ, Chen L (2017) Distributed publish/subscribe query processing on the spatio-textual data stream. In: ICDE, pp 1095–1106

  17. Chen L, Shang S, Zhang Z, Cao X, Jensen CS, Kalnis P (2018) Location-aware top-k term publish/subscribe. In: ICDE, pp 749–760

  18. Cong G, Jensen CS, Wu D (2009) Efficient retrieval of the top-k most relevant spatial web objects. PVLDB 2(1):337–348

    Google Scholar 

  19. Fariha A, Sarwar SM, Meliou A (2018) Squid: semantic similarity-aware query intent discovery. In: SIGMOD Conference 2018, pp 1745–1748

  20. Felipe ID, Hristidis V, Rishe N (2008) Keyword search on spatial databases. In: ICDE, pp 656–665

  21. Gao Y, Zhao J, Zheng B, Chen G (2016) Efficient collective spatial keyword query processing on road networks. IEEE Trans Intell Transp Syst 17(2):469–480

    Article  Google Scholar 

  22. Gunasekaran YD, Rahman MF, Hasani S, Zhang N, Das G (2018) DBLOC: density based clustering over location based services. In: SIGMOD, pp 1697–1700

  23. Han J, Wen J (2013) Mining frequent neighborhood patterns in a large labeled graph. In: CIKM, pp 259–268

  24. Han J, Wen J, Pei J (2014) Within-network classification using radius-constrained neighborhood patterns. In: CIKM, pp 1539–1548

  25. Han J, Zheng K, Sun A, Shang S, Wen J (2016) Discovering neighborhood pattern queries by sample answers in knowledge base. In: ICDE, pp 1014–1025

  26. Henao R, Li C, Carin L, Su Q, Shen D, Wang G, Wang W, Min MR, Zhang Y (2018) Baseline needs more love: on simple word-embedding-based models and associated pooling mechanisms. In: ACL, pp 440–450

  27. Jagadish HV, Ooi BC, Tan K, Yu C, Zhang R (2005) idistance: an adaptive b+-tree based indexing method for nearest neighbor search. In: TODS, vol 30, pp 364–397

  28. Li G, Xu J, Feng J (2012) Keyword-based k-nearest neighbor search in spatial databases. In: CIKM, pp 2144–2148

  29. Li F, Yao B, Tang M, Hadjieleftheriou M (2013) Spatial approximate string search. TKDE 25(6):1394–1409

    Google Scholar 

  30. Li M, Chen L, Cong G, Gu Y, Yu G (2016) Efficient processing of location-aware group preference queries. In: CIKM, pp 559–568

  31. Li X, Cheng Y, Cong G, Chen L (2017) Discovering pollution sources and propagation patterns in urban area. In: KDD, pp 1863–1872

  32. Liu H, Xu J, Zheng K, Liu C, Du L, Wu X (2017) Semantic-aware query processing for activity trajectories. In: WSDM, pp 283–292

  33. Liu A, Wang W, Shang S, Li Q, Zhang X (2018) Efficient task assignment in spatial crowdsourcing with worker and task privacy protection. GeoInformatica 22 (2):335–362

    Article  Google Scholar 

  34. Mahmood AR, Aref WG (2017) Query processing techniques for big spatial-keyword data. In: SIGMOD, pp 1777–1782

  35. Novak D, Batko M, Zezula P (2011) Metric index: an efficient and scalable solution for precise and approximate similarity search. Inf Syst 36(4):721–733

    Article  Google Scholar 

  36. Qian Z, Xu J, Zheng K, Sun W, Li Z, Guo H (2016) On efficient spatial keyword querying with semantics. In: DASFAA, pp 149–164

  37. Qian Z, Xu J, Zheng K, Zhao P, Zhou X (2018) Semantic-aware top-k spatial keyword queries. World Wide Web J 21(3):573–594

    Article  Google Scholar 

  38. Ray S, Blanco R, Goel AK (2017) High performance location-based services in a main-memory database. GeoInformatica 21(2):293–322

    Article  Google Scholar 

  39. Rocha-Junior JB, Gkorgkas O, Jonassen S, Nørvåg K (2011) Efficient processing of top-k spatial keyword queries. In: SSTD, pp 205–222

  40. Shang S, Ding R, Yuan B, Xie K, Zheng K, Kalnis P (2012) User oriented trajectory search for trip recommendation. In: EDBT’12, pp 156–167

  41. Shang S, Ding R, Zheng K, Jensen CS, Kalnis P, Zhou X (2014) Personalized trajectory matching in spatial networks. VLDB J 23(3):449–468

    Article  Google Scholar 

  42. Shang S, Liu J, Zheng K, Lu H, Pedersen TB, Wen J (2015) Planning unobstructed paths in traffic-aware spatial networks. GeoInformatica 19(4):723–746

    Article  Google Scholar 

  43. Shang S, Chen L, Wei Z, Guo D, Wen J (2016) Dynamic shortest path monitoring in spatial networks. J Comput Sci Technol 31(4):637–648

    Article  Google Scholar 

  44. Shang S, Chen L, Jensen CS, Wen J, Kalnis P (2017) Searching trajectories by regions of interest. IEEE Trans Knowl Data Eng 29(7):1549–1562

    Article  Google Scholar 

  45. Shang S, Chen L, Wei Z, Jensen CS, Zheng K, Kalnis P (2017) Trajectory similarity join in spatial networks. PVLDB 10(11):1178–1189

    Google Scholar 

  46. Shang S, Chen L, Wei Z, Jensen CS, Zheng K, Kalnis P (2018) Parallel trajectory similarity joins in spatial networks. VLDB J 27(3):395–420

    Article  Google Scholar 

  47. Shang S, Chen L, Zheng K, Jensen CS, Wei Z, Kalnis P (2019) Parallel trajectory-to-location join. IEEE Trans Knowl Data Eng 31(6):1194–1207

    Article  Google Scholar 

  48. Sun J, Xu J, Zheng K, Liu C (2017) Interactive spatial keyword querying with semantics. In: CIKM, pp 1727–1736

  49. Traina C Jr, Filho RFS, Traina AJM, Vieira MR, Faloutsos C (2007) The omni-family of all-purpose access methods: a simple and effective way to make similarity search more efficient. VLDB J 16(4):483–505

    Article  Google Scholar 

  50. Wang T, Li G, Feng J (2011) Efficient algorithms for top-k keyword queries on spatial databases. In: MDM, pp 285–286

  51. Xu J, Gao Y, Liu C, Zhao L, Ding Z (2015) Efficient route search on hierarchical dynamic road networks. Distrib Parallel Databases 33(2):227–252

    Article  Google Scholar 

  52. Yao B, Li F, Hadjieleftheriou M, Hou K (2010) Approximate string search in spatial databases. In: ICDE, pp 545–556

  53. Yue X, Xi M, Chen B, Gao M, He Y, Xu J (2019) A revocable group signatures scheme to provide privacy-preserving authentications. In: MONET

  54. Zhang C, Zhang Y, Zhang W, Lin X, Cheema MA, Wang X (2014) Diversified spatial keyword search on road networks. In: EDBT, pp 367–378

  55. Zhang D, Chan C, Tan K (2014) Processing spatial keyword query as a top-k aggregation query. In: SIGIR, pp 355–364

  56. Zhao K, Chen L, Cong G (2016) Topic exploration in spatio-temporal document collections. In: SIGMOD, pp 985–998

  57. Zhao K, Liu Y, Yuan Q, Chen L, Chen Z, Cong G (2016) Towards personalized maps: mining user preferences from geo-textual data. PVLDB 9(13):1545–1548

    Google Scholar 

  58. Zhao J, Gao Y, Chen G, Chen R (2018) Why-not questions on top-k geo-social keyword queries in road networks. In: ICDE 2018, pp 965–976

  59. Zheng K, Su H, Zheng B, Shang S, Xu J, Liu J, Zhou X (2015) Interactive top-k spatial keyword queries. In: ICDE, pp 423–434

  60. Zheng K, Zheng B, Xu J, Liu G, Liu A, Li Z (2017) Popularity-aware spatial keyword search on activity trajectories. World Wide Web 20(4):749–773

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61872258, 61572335, 61772356, 61876117, and 61802273, the Dongguan Innovative Research Team Program under grant number 2018607201008, the Australian Research Council discovery projects under grant numbers DP160102412, DP170104747, DP180100212, and the Open Program of State Key Laboratory of Software Architecture under item number SKLSAOP1801.

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Authors and Affiliations

  1. Institute of Artificial Intelligence, School of Computer Science and Technology, Soochow University, Suzhou, China

    Xinyu Chen, Jiajie Xu, Pengpeng Zhao, Junhua Fang & Lei Zhao

  2. Neusoft Corporation, Shenyang, China

    Xinyu Chen & Pengpeng Zhao

  3. Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China

    Jiajie Xu

  4. Faculty of SET, Swinburne University of Technology, Melbourne, Australia

    Rui Zhou & Chengfei Liu

  5. University of Electronic Science and Technology of China, Chengdu, China

    Junhua Fang

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  1. Xinyu Chen
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Correspondence to Jiajie Xu, Rui Zhou or Pengpeng Zhao.

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Chen, X., Xu, J., Zhou, R. et al. S2R-tree: a pivot-based indexing structure for semantic-aware spatial keyword search. Geoinformatica 24, 3–25 (2020). https://doi.org/10.1007/s10707-019-00372-z

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