, Volume 20, Issue 3, pp 453–469 | Cite as

Skyline for geo-textual data

  • Jianing Li
  • Hongzhi WangEmail author
  • Jianzhong Li
  • Hong Gao


Massive amount of data that are associated with geographic information are generated in Internet. More and more researches focus on how to retrieve geo-textual data effectively. Existing methods mostly allow exact matches for query keywords but fail to support fuzzy preference queries. In this paper, we study the skyline problem of fuzzy preference queries. That is, given a set of geo-textual data, the skyline comprises the objects that are not dominated by others. In this paper, we only consider the problem of two dimensions, the text relevance dimension and the spatial relevance dimension. We introduce two functions to quantify the text relevance and the spatial relevance. We also develop a new index structure to organize the geo-textual data and an algorithm based on it. Theoretical analysis and experimental results show that our method offers scalability and good performance.


Geo-textual data Skyline Fuzzy Text relevance Spatial relevance 



This paper was supported by NGFR 973 grant 2012CB316200, NSFC grant 61472099, 61133002 and National Sci-Tech Support Plan 2015BAH10F01.


  1. 1.
    Bao J, Mokbel MF (2013) GeoRank: an efficient location-aware news feed ranking system. In: SIGSPATIA/L GIS 2013. 184–193. ACM, OrlandoGoogle Scholar
  2. 2.
    Lisi C, Gao C, Xin C (2013) An efficient query indexing mechanism for filtering geo-textual data. In: SIGMOD 2013. 749–760. ACM, NewYorkGoogle Scholar
  3. 3.
    Long G, Jie S, Htoo Htet A, Kian-Lee T (2015) Efficient continuous top-k spatial keyword queries on road networks. GeoInformatica 19(1):29–60CrossRefGoogle Scholar
  4. 4.
    Huang W, Li G, Tan K-L, Feng J (2012) Efficient safe-region construction for moving top-K spatial keyword queries. In: CIKM 2012. 932–941. ACM, MauiGoogle Scholar
  5. 5.
    Chen L, Cong G, Cao X, Tan K-L (2015) Temporal Spatial-Keyword Top-k publish/subscribe. In: ICDE 2015. 255–266. ICDE Press, SeoulGoogle Scholar
  6. 6.
    Zheng K, Su H, Zheng B, Shang S, Xu J, Liu J, Zhou X (2015) Interactive Top-k Spatial Keyword queries. In: ICDE 2015. 423–434. ICDE Press, SeoulGoogle Scholar
  7. 7.
    Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen: Efficient Reverse Top-k Boolean Spatial Keyword Queries on Road Networks. IEEE Trans. Knowl. Data Eng. (TKDE) 27(5):1205–1218 (2015)Google Scholar
  8. 8.
    Zhang D, Chan C-Y, Tan K-L (2014) Processing spatial keyword query as a top-k aggregation query. In: SIGIR 2014. 355–364. ACM, Gold CoastGoogle Scholar
  9. 9.
    Chen L, Lin X, Hu H, Jensen CS, Xu J (2015) Answering why-not questions on spatial keyword top-k queries. In: ICDE 2015. 279–290. ICDE Press, SeoulGoogle Scholar
  10. 10.
    Tan KL, Eng PK, Ooi BC (2001) Efficient progressive skyline computation. In: VLDB 2001. 301–310. ACM, RomaGoogle Scholar
  11. 11.
    Dellis E, Seeger B (2007) Efficient computation of reverse skyline queries. In: VLDB 2007. 291–302. ACM, ViennaGoogle Scholar
  12. 12.
    Borzsonyi S, Kossmann D, Stocker K (2001) The skyline operator. In: ICDE 2001. 421–430. ICDE Press, HeidelbergGoogle Scholar
  13. 13.
    De Felipe I, Hristidis V, Rishe N (2008) Keyword search on spatial databases. In: ICDE 2008. 656–665. ICDE Press, WashingtonGoogle Scholar
  14. 14.
    Zhang D, Chee YM, Mondal A, Tung AKH, Kitsuregawa M (2009) Keyword search in spatial databases: Towards Searching by Document. In: ICDE 2009. 688–699. ICDE Press, ShanghaiGoogle Scholar
  15. 15.
    Chen YY, Suel T, Markowetz A (2006) Efficient query processing in geographic web search engines. In: SIGMOD 2006. 277–288. ACM, ChicagoGoogle Scholar
  16. 16.
    De Felipe I, Hristidis V, Rishe N (2008) Keyword search on spatial databases. In: ICDE 2008. 656–665. ICDE Press, CancúnGoogle Scholar
  17. 17.
    Li G, Xu J, Feng J (2012) Keyword-based k-nearest neighbor search in spatial databases. In: CIKM 2012. 2144–2148. ACM, MauiGoogle Scholar
  18. 18.
    Xin C, Gao C, Tao G, Jensen CS, Beng Chin O (2015) Efficient processing of spatial group keyword queries. ACM trans. Database Syst (TODS) 40(2):13Google Scholar
  19. 19.
    Dingming W, Man Lung Y, Jensen CS (2013) Moving spatial keyword queries: Formulation, methods, and analysis. ACM Trans. Database Syst (TODS) 38(1):7Google Scholar
  20. 20.
    Wang X, Zhang Y, Zhang W, Lin X, Wang W (2015) AP-Tree: Efficiently support continuous spatial-keyword queries over stream. In: ICDE 2015. 1107–1118. ICDE Press, SeoulGoogle Scholar
  21. 21.
    Ying L, Jiaheng L, Gao C, Wei W, Cyrus S (2014) Efficient algorithms and cost models for reverse spatial-keyword k-nearest neighbor search. ACM trans. Database Syst (TODS) 39(2):13Google Scholar
  22. 22.
    Khodaei A, Shahabi C (2012) Chen Li: SKIF-P: a point-based indexing and ranking of web documents for spatial-keyword search. GeoInformatica 16(3):563–596CrossRefGoogle Scholar
  23. 23.
    Jun H, Ju F, Guoliang L, Shanshan C (2012) Top-k Fuzzy Spatial Keyword Search. (in Chinese). Chin J Comput 35(11):2237–2246CrossRefGoogle Scholar
  24. 24.
    Cong G, Jensen CS, Wu D (2009) Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects. In: VLDB 2009. 337–348. ACM, LyonGoogle Scholar
  25. 25.
    Li G, Feng J, Xu J (2012) DESKS: Direction-Aware Spatial Keyword Search. In: ICDE 2012. 474–485. ICDE Press, WashingtonGoogle Scholar
  26. 26.
    Zhang C, Zhang Y, Zhang W, Lin X (2013) Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search. In: ICDE 2013. 901–912. ICDE Press, BrisbaneGoogle Scholar
  27. 27.
    Yao B, Li F, Hadjieleftheriou M, Hou K (2010) Approximate string search in spatial databases. In: ICDE 2010. 545–556. ICDE Press, Long BeachGoogle Scholar
  28. 28.
    Hadjieleftheriou M, Li C (2009) Efficient approximate search on string collections. In: VLDB 2009. 1660–1661. ACM, LyonGoogle Scholar
  29. 29.
    Li C, Lu J, Lu Y (2008) Efficient merging and filtering algorithms for approximate string searches. In: ICDE 2008. 257–266. ICDE Press, CancúnGoogle Scholar
  30. 30.
    Xiao C, Wang W, Lin X, Shang H (2009) Top-k set similarity joins. In: ICDE 2009. 916–927. ICDE Press, ShanghaiGoogle Scholar
  31. 31.
    Kossmann D, Ramsak F, Rost S (2002) Shooting stars in the sky: an online algorithm for skyline queries. In: VLDB 2002. 275–286. ACM, Hong KongGoogle Scholar
  32. 32.
    Papadias D, Fu G, Seeger B, Tao Y (2003) An optimal and progressive algorithm for skyline queries. In: SIGMOD 2003. 467–478. ACM, San DiegoGoogle Scholar
  33. 33.
    Lee J, Hwang S-W (2014) Toward efficient multidimensional subspace skyline computation. In: VLDB 2014. 129–145. ACM, HangzhouGoogle Scholar
  34. 34.
    Liu B, Chan C-Y (2010) ZINC: Efficient indexing for skyline computation. In: VLDB 2010. 197–207. ACM, SingaporeGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Jianing Li
    • 1
  • Hongzhi Wang
    • 1
    Email author
  • Jianzhong Li
    • 1
  • Hong Gao
    • 1
  1. 1.Department of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina

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