Electronic commerce commodity entity identities based on hierarchical probability model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
http://link.springer.com/content/pdf/10.1007/s10586-017-1437-8.pdf
Reference20 articles.
1. Fang, Q., Hu, Y., Lv, S., Guo, L., Xiao, L. Hu, Y.: IIRS: A Novel Framework of Identifying Commodity Entities on E-commerce Big Data. Web-Age Information Management. Lecture Notes in Computer Science, vol. 9098, pp. 473–480 (2015)
2. Altwaijry, H., Mehrotra, S., Kalashnikov, D.V.: QuERy: a framework for integrating entity resolution with query processing. Proc. VLDB Endow. 9(3), 120–131 (2015)
3. Li, L., Wang, H., Gao, H., Li, J.: EIF: A Framework of Effective Entity Identification. Web-Age Information Management. Lecture Notes in Computer Science, vol. 6184, pp. 717–728 (2015)
4. Fan, W., Gao, H., Jia, X., Li, J., Ma, S.: Dynamic constraints for record matching. VLDB J. 20(4), 495–520 (2011)
5. Deng, D., Li, G., Feng, J., Duan, Y., Gong, Z.: A unified framework for approximate dictionary-based entity extraction. VLDB J. 24(1), 143–167 (2015)
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