EPEMS: An entity matching system for E-commerce products

Lei Gao, Pengpeng Zhao, Victor S. Sheng, Zhixu Li, An Liu, Jian Wu, Zhiming Cui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 17th Asia-PacificWeb Conference,APWeb 2015, Proceedings
EditorsReynold Cheng, Bin Cui, Zhenjie Zhang, Ruichu Cai, Jia Xu
PublisherSpringer-Verlag
Pages871-874
Number of pages4
ISBN (Print)9783319252544
DOIs
StatePublished - 2015
Event17th Asia-PacificWeb Conference, APWeb 2015 - Guangzhou, China
Duration: Sep 18 2015Sep 20 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9313
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Asia-PacificWeb Conference, APWeb 2015
CountryChina
CityGuangzhou
Period09/18/1509/20/15

Keywords

  • Blocking
  • E-commerce Data
  • Entity matching
  • Picture similarity

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  • Cite this

    Gao, L., Zhao, P., Sheng, V. S., Li, Z., Liu, A., Wu, J., & Cui, Z. (2015). EPEMS: An entity matching system for E-commerce products. In R. Cheng, B. Cui, Z. Zhang, R. Cai, & J. Xu (Eds.), Web Technologies and Applications - 17th Asia-PacificWeb Conference,APWeb 2015, Proceedings (pp. 871-874). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9313). Springer-Verlag. https://doi.org/10.1007/978-3-319-25255-1_74