Advertisement

Analyzing Temporal Keyword Queries for Interactive Search over Temporal Databases

  • Qiao Gao
  • Mong Li Lee
  • Tok Wang Ling
  • Gillian Dobbie
  • Zhong Zeng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11029)

Abstract

Querying temporal relational databases is a challenge for non-expert database users, since it requires users to understand the semantics of the database and apply temporal joins as well as temporal conditions correctly in SQL statements. Traditional keyword search approaches are not directly applicable to temporal relational databases since they treat time-related keywords as tuple values and do not consider the temporal joins between relations, which leads to missing answers, incorrect answers and missing query interpretations. In this work, we extend keyword queries to allow the temporal predicates, and design a schema graph approach based on the Object-Relationship-Attribute (ORA) semantics. This approach enables us to identify temporal attributes of objects/relationships and infer the target temporal data of temporal predicates, thus improving the completeness and correctness of temporal keyword search and capturing the various possible interpretations of temporal keyword queries. We also propose a two-level ranking scheme for the different interpretations of a temporal query, and develop a prototype system to support interactive keyword search.

References

  1. 1.
    Allen, J.F.: Maintaining knowledge about temporal intervals. CACM 26, 832–843 (1983)CrossRefGoogle Scholar
  2. 2.
    de Oliveira, P., da Silva, A., de Moura, E.: Ranking candidate networks of relations to improve keyword search over relational databases. In: ICDE (2015)Google Scholar
  3. 3.
    Ding, B., Yu, J.X., Wang, S., Qin, L., Zhang, X., Lin, X.: Finding top-k min-cost connected trees in databases. In: ICDE (2007)Google Scholar
  4. 4.
    Gao, Q., Lee, M.L., Ling, T.W., Dobbie, G., Zeng, Z.: Analyzing temporal keyword queries for interactive search over temporal databases. Technical report TRA3/18. National University of Singapore (2018)Google Scholar
  5. 5.
    Gunadhi, H., Segev, A.: Query processing algorithms for temporal intersection joins. In: ICDE (1991)Google Scholar
  6. 6.
    Hristidis, V., Hwang, H., Papakonstantinou, Y.: Authority-based keyword search in databases. ACM TODS 33(1), 1:1–1:40 (2008)CrossRefGoogle Scholar
  7. 7.
    Hristidis, V., Papakonstantinou, Y.: DISCOVER: keyword search in relational databases. In: VLDB (2002)Google Scholar
  8. 8.
    Hulgeri, A., Nakhe, C.: Keyword searching and browsing in databases using BANKS. In: ICDE (2002)Google Scholar
  9. 9.
    Jia, X., Hsu, W., Lee, M.L.: Target-oriented keyword search over temporal databases. In: Hartmann, S., Ma, H. (eds.) DEXA 2016. LNCS, vol. 9827, pp. 3–19. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-44403-1_1CrossRefGoogle Scholar
  10. 10.
    Kacholia, V., Pandit, S., Chakrabarti, S.: Bidirectional expansion for keyword search on graph databases. In: VLDB (2005)Google Scholar
  11. 11.
    Kargar, M., An, A., Cercone, N., Godfrey, P., Szlichta, J., Yu, X.: Meaningful keyword search in relational databases with large and complex schema. In: ICDE (2015)Google Scholar
  12. 12.
    Liu, F., Yu, C., Meng, W., Chowdhury, A.: Effective keyword search in relational databases. In: ACM SIGMOD (2006)Google Scholar
  13. 13.
    Liu, Z., Wang, C., Chen, Y.: Keyword search on temporal graphs. TKDE 29(8), 1667–1680 (2017)Google Scholar
  14. 14.
    Luo, Y., Lin, X., Wang, W., Zhou, X.: SPARK: top-k keyword query in relational databases. In: ACM SIGMOD (2007)Google Scholar
  15. 15.
    Qin, L., Yu, J.X., Chang, L.: Keyword search in databases: the power of RDBMS. In: ACM SIGMOD (2009)Google Scholar
  16. 16.
    Yu, X., Shi, H.: CI-Rank: ranking keyword search results based on collective importance. In: ICDE (2012)Google Scholar
  17. 17.
    Zeng, Z., Bao, Z., Le, T.N., Lee, M.L., Ling. T.W.: ExpressQ: identifying keyword context and search target in relational keyword queries. In: ACM CIKM (2014)Google Scholar
  18. 18.
    Zeng, Z., Bao, Z., Lee, M.L., Ling, T.W.: A semantic approach to keyword search over relational databases. In: ER (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Qiao Gao
    • 1
  • Mong Li Lee
    • 1
  • Tok Wang Ling
    • 1
  • Gillian Dobbie
    • 2
  • Zhong Zeng
    • 3
  1. 1.National University of SingaporeSingaporeSingapore
  2. 2.University of AucklandAucklandNew Zealand
  3. 3.Data Center Technology Lab, HuaweiHangzhouChina

Personalised recommendations