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Thesaurus matching in electronic commerce

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Abstract

This paper tackles the problem of e-commerce thesauri alignment. It includes the definition of three alignment techniques which can be combined to increase the effectiveness and reduce the execution time. It also introduces a filtering technique to reduce the number of candidates returned to the final user. This work reports a set of evaluations that were lead with real-world data. Results show that the proposed techniques outperform schema, the state-of-the-art approach. They also drastically reduce the execution time, thus making them more usable in real-world applications.

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Notes

  1. https://www.google.com/shopping.

  2. https://www.amazon.com.

  3. http://www.criteo.com.

  4. http://wordnet.princeton.edu.

  5. https://www.google.com/basepages/producttype/taxonomy.en-US.txt.

  6. https://www.researchgate.net/publication/334163680.

  7. https://github.com/nudge/schema.

References

  1. Aanen, S., Nederstigt, L., Vandic, D., & Frasincar, F. (2012). Mapping product taxonomies in e-commerce. Rotterdam: Technical report, Econometric Institute, Erasmus University Rotterdam.

    Google Scholar 

  2. Aanen, S. S., Nederstigt, L. J., Vandić, D., & Frăsincar, F. (2012). SCHEMA - An algorithm for automated product taxonomy mapping in E-commerce (pp. 300–314). Berlin, Heidelberg: Springer.

    Google Scholar 

  3. Aanen, S. S., Vandic, D., & Frasincar, F. (2015). Automated product taxonomy mapping in an e-commerce environment. Expert Systems with Applications, 42(3), 1298–1313.

    Article  Google Scholar 

  4. Bellahsene, Z., Bonifati, A., & Rahm, E. (Eds.). (2011). Schema matching and mapping., Data-centric systems and applications Berlin: Springer.

    Google Scholar 

  5. Cruz, I. F., Antonelli, F. P., & Stroe, C. (2009). Agreementmaker: Efficient matching for large real-world schemas and ontologies. Proceeding of VLDB Endowment, 2(2), 1586–1589.

    Article  Google Scholar 

  6. Cruz, I. F., & Sunna, W. (2008). Structural alignment methods with applications to geospatial ontologies. Transactions of GIS, 12, 683–711.

    Article  Google Scholar 

  7. David, J. (2007). AROMA: An implicative ontology matching method based on the association rule model., Theses Nantes: Université de Nantes.

    Google Scholar 

  8. David, J., Guillet, F., & Briand, H. (2006). Matching directories and owl ontologies with aroma. In Proceedings of the 15th ACM international conference on information and knowledge management, CIKM ’06 (pp. 830–831). New York, NY: ACM.

  9. Euzenat, J., & Shvaiko, P. (2007). Ontology matching. Berlin: Springer.

    Google Scholar 

  10. Kim, W., Park, S., Bang, S., & Lee, S. (2006). An ontology mapping algorithm between heterogeneous product classification taxonomies. In Proceedings of the 1st international conference on ontology matching (pp. 221–225).

  11. Levenshtein, V. I. (1966). Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady, 10(8), 707–710.

    Google Scholar 

  12. Miller, G. A. (1995). Wordnet: A lexical database for English. Communications ACM, 38(11), 39–41.

    Article  Google Scholar 

  13. Nederstigt, L., Vandic, D., & Frasincar, F. (2012). An automated approach to product taxonomy mapping in e-commerce (pp. 111–120). Berlin, Heidelberg: Springer.

    Google Scholar 

  14. Nederstigt, L. J., Aanen, S. S., Vandić, D., & Frăsincar, F. (2012). An automatic approach for mapping product taxonomies in e-commerce systems (pp. 334–349). Berlin, Heidelberg: Springer.

    Google Scholar 

  15. Noy, N. F., & Musen, M. A.. (2001) Anchor-prompt: Using non-local context for semantic matching. In Proceedings of the workshop on ontologies and information sharing the international joint conference on artificial intelligence (pp. 63–70).

  16. Noy, N. F., & Musen, M. A. (2003). The PROMPT suite: Interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies, 59(6), 983–1024.

    Article  Google Scholar 

  17. Park, S., & Kim, W. (2007). Ontology mapping between heterogeneous product taxonomies in an electronic commerce environment. International Journal of Electronic Commerce, 12, 69–87.

    Article  Google Scholar 

  18. Shvaiko, P. (2005). A classification of schema-based matching approaches. Journal of Data Semantics, 4, 146–171.

    Google Scholar 

  19. Sunna, W., & Cruz, I. F. (2007). Structure-based methods to enhance geospatial ontology alignment. In Proceedings of the 2nd international conference on GeoSpatial semantics, GeoS’07 (pp. 82–97). Berlin: Springer.

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Authors and Affiliations

  1. Lengow, Nantes, France

    Thomas Cerqueus, Jonathan Bonnaud & Oleksandr Dashkov

  2. LS2N - University of Nantes, CNRS, Nantes, France

    Emmanuel Morin

Authors
  1. Thomas Cerqueus
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  2. Jonathan Bonnaud
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  3. Oleksandr Dashkov
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  4. Emmanuel Morin
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Correspondence to Thomas Cerqueus.

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Cerqueus, T., Bonnaud, J., Dashkov, O. et al. Thesaurus matching in electronic commerce. Electron Commer Res 22, 513–538 (2022). https://doi.org/10.1007/s10660-020-09438-9

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