Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping

The problem of record linkage focuses on determining whether two object descriptions refer to the same underlying entity. Addressing this problem effectively has many practical applications, e.g., elimination of duplicate records in databases and citation matching for scholarly articles. In this paper, we consider a new domain where the record linkage problem is manifested: Internet comparison shopping. We address the resulting linkage setting that requires learning a similarity function between record pairs from streaming data. The learned similarity function is subsequently used in clustering to determine which records are co-referent and should be linked. We present an online machine learning method for addressing this problem, where a composite similarity function based on a linear combination of basis functions is learned incrementally. We illustrate the efficacy of this approach on several real-world datasets from an Internet comparison shopping site, and show that our method i...

• Type: Conference
• Year: 2005
• Where: ICDM
• Authors: Mikhail Bilenko, Sugato Basu, Mehran Sahami
• Keywords: Data Mining, ICDM 2005, Internet Comparison Shopping, Record Linkage, Similarity Function