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EPEMS: An Entity Matching System for E-Commerce Products

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Web Technologies and Applications (APWeb 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9313))

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Abstract

Entity Matching is used to identify records representing the same entities in the real world. As e-commerce is developing rapidly, online products grow explosively in both amount and variety. Applying entity matching to e-commerce data and finding records representing the same products make customers convenient to compare prices. This paper proposes an entity matching system for e-commerce data, called EPEMS. Compared with existing systems, we improve an existing sorted neighborhood blocking method, which is used to reduce the number of comparisons. At the same time the similarity of product pictures is used to improve matching results.

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References

  1. Christen, P.: A survey of indexing techniques for scalable record linkage and deduplication. IEEE Transactions on Knowledge and Data Engineering 24(9), 1537–1555 (2012)

    Article  Google Scholar 

  2. Hernández, M.A., Stolfo, S.J.: The merge/purge problem for large databases. ACM SIGMOD Record 24, 127–138 (1995)

    Article  Google Scholar 

  3. Warshall, S.: A theorem on boolean matrices. Journal of the ACM (JACM) 9(1), 11–12 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  4. Draisbach, U., Naumann, F., Szott, S., Wonneberg, O.: Adaptive windows for duplicate detection. In: 2012 IEEE 28th International Conference on Data Engineering (ICDE), pp. 1073–1083. IEEE (2012)

    Google Scholar 

  5. Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2161–2168. IEEE (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, 215006, P.R. China

    Lei Gao, Pengpeng Zhao, Zhixu Li, An Liu, Jian Wu & Zhiming Cui

  2. Computer Science Department, University of Central Arkansas, Conway, USA

    Victor S. Sheng

Authors
  1. Lei Gao
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  2. Pengpeng Zhao
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  3. Victor S. Sheng
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  4. Zhixu Li
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  5. An Liu
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  6. Jian Wu
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  7. Zhiming Cui
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Editor information

Editors and Affiliations

  1. University of Hong Kong, Hong Kong, China

    Reynold Cheng

  2. Computer Science, Peking University, Beijing, China

    Bin Cui

  3. Advanced Digital Sciences Center (ADSC), Singapore, Singapore

    Zhenjie Zhang

  4. University of Technology, Guangzhou, China

    Ruichu Cai

  5. Guangxi University, Guangxi, China

    Jia Xu

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© 2015 Springer International Publishing Switzerland

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Gao, L. et al. (2015). EPEMS: An Entity Matching System for E-Commerce Products. In: Cheng, R., Cui, B., Zhang, Z., Cai, R., Xu, J. (eds) Web Technologies and Applications. APWeb 2015. Lecture Notes in Computer Science(), vol 9313. Springer, Cham. https://doi.org/10.1007/978-3-319-25255-1_74

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  • DOI: https://doi.org/10.1007/978-3-319-25255-1_74

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25254-4

  • Online ISBN: 978-3-319-25255-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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