Skip to main content
SpringerLink
Log in

Weight-Adjustable Ranking for Keyword Search in Relational Databases

  • Conference paper
  • First Online:
Intelligent and Interactive Computing

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 67))

  • 701 Accesses

Abstract

Huge volumes of invaluable information are hidden behind web relational databases. They could not be extracted by search engines. The problem is especially severe for long text data, for example, book reviews, company descriptions, and product specifications. Many researches have investigated to integrate information retrieval and database indexing technologies to provide keyword search functionality for these useful contents. Due to diversifying data relationships in application domains and miscellaneous personal preferences, current ranking results of related researches do not satisfy user requirements. We design and implement a Weight-Adjustable Ranking for Keyword Search (WARKS) system to address the issue. Mean average precision (MAP) and mean rank reciprocal difference (MRRD) are proposed as measurements of ranking effectiveness. We use an integrated international trade show database as our experimental domain. User study demonstrates that WARKS performs better than previous practices.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agrawal S, Chaudhuri S, Das G (2002) DBXplorer: a system for keyword-based search over relational databases. In: Proceedings of the 18th IEEE international conference on data engineering (ICDE 2002), pp 5–16

    Google Scholar 

  2. Balmin A, Hristidis V, Papakonstantinou Y (2004) Objectrank: authority-based keyword search in databases. In: Proceedings of the 30th international conference on very large data bases (VLDB’04), pp 564–575

    Google Scholar 

  3. Bergamaschi S, Domnori E, Guerra F, Orsini M, Lado RT, Velegrakis Y (2010) Keymantic: semantic keyword-based searching in data integration systems. Proc VLDB Endowment 3(1–2):1637–1640

    Article  Google Scholar 

  4. Bergamaschi S, Guerra F, Simonini G (2014) Keyword search over relational databases: issues, approaches and open challenges. In: Lecture notes in computer science, vol 8173, pp 54–73

    Google Scholar 

  5. Bergamaschi S, Guerra F, Interlandi M, Lado RT, Velegrakis Y (2016) Combining user and database perspective for solving keyword queries over relational databases. Inf Syst 55:1–19

    Article  Google Scholar 

  6. Bhalotia G, Hulgeri A, Nakhe C, Chakrabarti S, Sudarshan S (2002) Keyword searching and browsing in databases using BANKS. In: Proceedings of the 18th IEEE international conference on data engineering (ICDE 2002), pp 431–440

    Google Scholar 

  7. Coffman J, Weaver AC (2010) A framework for evaluating database keyword search strategies. In: Proceedings of the 19th ACM international conference on information and knowledge management, pp 729–738

    Google Scholar 

  8. Hristidis V, Papakonstantinou Y (2002) DISCOVER: Keyword search in relational databases. In: Proceedings of VLDB’02. VLDB Endowment, Aug 2002, pp 670–681

    Chapter  Google Scholar 

  9. Hristidis V, Gravano L, Papakonstantinou Y (2003) Efficient IR-style keyword search over relational databases. In: Proceedings of VLDB’03, pp 850–861

    Chapter  Google Scholar 

  10. Jabeur LB, Soulier L, Tamine L, Mousset P (2016) A product feature-based user-centric ranking model for e-commerce search. In: Lecture notes in computer science, vol 9822, pp 174–186

    Google Scholar 

  11. Kacholia V, Pandit S, Chakrabarti S, Sudarshan S, Desai R, Karambelkar H (2005) Bidirectional expansion for keyword search on graph databases. In: Proceedings of the 31st international conference on very large data bases (VLDB’05), pp 505–516

    Google Scholar 

  12. Liu F, Yu C, Meng W, Chowdhury A (2006) Effective keyword search in relational databases. In: Proceedings of ACM SIGMOD’06, pp 563–574

    Google Scholar 

  13. Liu Z, Wang C, Chen Y (2017) Keyword search on temporal graphs. IEEE Trans Knowl Data Eng 29(8):1667–1680

    Article  Google Scholar 

  14. Simitsis A, Koutrika G, Ioannidis YE (2008) Precis: from unstructured keywords as queries to structured databases as answers. VLDB J 17(1):117–149

    Article  Google Scholar 

  15. Zhu L, Du X, Ma Q, Meng W, Liu H (2018) Keyword search with real-time entity resolution in relational databases. In: Proceedings of the 2018 10th international conference on machine learning and computing, pp 134–139

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Management, Tamkang University, New Taipei City, Taiwan

    Chichang Jou

  2. Department of Computing and Information Systems, Sunway University, Petaling Jaya, Malaysia

    Sian Lun Lau

Authors
  1. Chichang Jou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sian Lun Lau
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chichang Jou .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Milan, Milan, Italy

    Vincenzo Piuri

  2. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Sikkim, India

    Samarjeet Borah

  4. Department of Intelligent Computing and Analytics, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka, Malaysia

    Sharifah Sakinah Syed Ahmad

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jou, C., Lau, S.L. (2019). Weight-Adjustable Ranking for Keyword Search in Relational Databases. In: Piuri, V., Balas, V., Borah, S., Syed Ahmad, S. (eds) Intelligent and Interactive Computing. Lecture Notes in Networks and Systems, vol 67. Springer, Singapore. https://doi.org/10.1007/978-981-13-6031-2_31

Download citation

Publish with us

Policies and ethics

Search

Navigation