Skip to main content
SpringerLink
Log in

Graph Matching Based Semantic Search Engine

  • Conference paper
  • First Online:
Metadata and Semantic Research (MTSR 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 846))

Included in the following conference series:

Abstract

Explosive growth of the Web has made searching Web data a challenging task for information retrieval systems. Semantic search systems that go beyond the shallow keyword matching approaches and map words to their conceptual meaning representations offer better results to the users. On the other hand, a lot of representation formats have been specified to represent Web data into a semantic format. We propose a search engine for searching Web data represented in UNL (Universal Networking Language). UNL has numerous attractive features to support semantic search. One of the main features is that UNL does not depend on domain ontology. Our proposed search engine is based on semantic graph matching. It includes semantic expansion for graph nodes and relation matching based on relation meaning. The search results are ranked depending on the semantic similarity between the user query and the retrieved documents. We developed a prototype implementing the proposed semantic search engine, and our evaluations demonstrate its effectiveness across a wide-range of semantic search tasks.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Kobayashi, M., Takeda, K.: Information retrieval on the web. ACM Comput. Surv. (CSUR) 32(2), 144–173 (2000)

    Article  Google Scholar 

  2. Blanco, R., Mika, P., Vigna, S.: Effective and efficient entity search in RDF data. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 83–97. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25073-6_6

    Chapter  Google Scholar 

  3. Li, Y., Wang, Y., Huang, X.: A relation-based search engine in semantic web. IEEE Trans. Knowl. Data Eng. 19(2), 273–282 (2007)

    Article  Google Scholar 

  4. Ding, L., et al.: Swoogle: a semantic web search and metadata engine. In: Proceedings of 13th ACM Conference on Information and Knowledge Management, November 2004

    Google Scholar 

  5. Caetano, T.S., Cheng, L., Le, Q.V., Smola, A.J.: Learning graph matching, pattern analysis and machine. Intelligence 31(6), 1048–1058 (2009)

    Google Scholar 

  6. Tümer, D., Shah, M.A., Bitirim, Y.: An empirical evaluation on semantic search performance of keyword-based and semantic search engines: Google, Yahoo, Msn and Hakia. In: 2009 4th International Conference on Internet Monitoring and Protection (ICIMP 2009) (2009)

    Google Scholar 

  7. Guobing, Z., Bofeng, Z., Yanglan, G., Jianwen, Z.: An ontology-based methodology for semantic expansion search. In: Fifth International Conference on Fuzzy Systems and Knowledge Discovery, vol. 5, pp. 453–457 (2008)

    Google Scholar 

  8. Farouk, M., Ishizuka, M.: CDL-based semantic representation for dynamic web pages. Int. J. Semant. Comput. 6(1), 51–65 (2012)

    Article  Google Scholar 

  9. Gong, Z., Cheang, C.W., Hou U, L.: Multi-term web query expansion using wordnet. In: Bressan, S., Küng, J., Wagner, R. (eds.) DEXA 2006. LNCS, vol. 4080, pp. 379–388. Springer, Heidelberg (2006). https://doi.org/10.1007/11827405_37

    Chapter  Google Scholar 

  10. Pfeiffer, H.D., Hartley, R.T.: A comparison of different conceptual structures projection algorithms. ICCS 2007, 165–178 (2007)

    MATH  Google Scholar 

  11. Alansary, S., Nagi, M.: From language implicit structure to UNL explicit knowledge infrastructure. In: The International Symposium on Natural Language Processing SNLP 2013, Phuket, Thailand, 28–30 October 2013 (2013)

    Google Scholar 

  12. Alansary, S., Nagi, M., Adly, N.: Machine translation using the universal networking language (UNL). In: 8th International Conference on Language Engineering. Ain Shams University, Egypt (2008)

    Google Scholar 

  13. Adly, N., Al Ansary, S.: Evaluation of arabic machine translation system based on the universal networking language. In: Horacek, H., Métais, E., Muñoz, R., Wolska, M. (eds.) NLDB 2009. LNCS, vol. 5723, pp. 243–257. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-12550-8_20

    Chapter  Google Scholar 

  14. Lee, J., Min, J.-K., Alice, O., Chung, C.-W.: Effective ranking and search techniques for Web resources considering semantic relationships. Inf. Process. Manag.: Int. J. 50(1), 132–155 (2014)

    Article  Google Scholar 

  15. Ullmann, J.R.: An algorithm for subgraph isomorphism. J. Assoc. Comput. Mach. 23(I), 31–42 (1976)

    Article  MathSciNet  Google Scholar 

  16. Messmer, B.T., Bunke, H.: Efficient subgraph isomorphism detection: a decomposition approach. IEEE Trans. Knowl. Data Eng. 12(2), 307–323 (2000)

    Article  Google Scholar 

  17. Mangold, C.: A survey and classification of semantic search approaches. Int. J. Metadata Semant. Ontol. 2(1), 23–34 (2007)

    Article  Google Scholar 

  18. Ensan, F., Bagheri, E.: Document retrieval model through semantic linking. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, Cambridge, United Kingdom (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Faculty of Computers and Information, Assiut University, Assiut, Egypt

    Mamdouh Farouk

  2. National Institute of Informatics, Tokyo, Japan

    Mitsuru Ishizuka

  3. Department of Computer Science, University of Liverpool, Liverpool, UK

    Danushka Bollegala

Authors
  1. Mamdouh Farouk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mitsuru Ishizuka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Danushka Bollegala
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mamdouh Farouk .

Editor information

Editors and Affiliations

  1. Alexander Technological Educational Institute (ATEI) of Thessaloniki, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Fabio Sartori

  3. Alexander Technological Educational Institute (ATEI) of Thessaloniki, Thessaloniki, Greece

    Rania Siatri

  4. Library and Information Services, Cyprus University of Technology, Limassol, Cyprus

    Marios Zervas

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Farouk, M., Ishizuka, M., Bollegala, D. (2019). Graph Matching Based Semantic Search Engine. In: Garoufallou, E., Sartori, F., Siatri, R., Zervas, M. (eds) Metadata and Semantic Research. MTSR 2018. Communications in Computer and Information Science, vol 846. Springer, Cham. https://doi.org/10.1007/978-3-030-14401-2_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-14401-2_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14400-5

  • Online ISBN: 978-3-030-14401-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation