Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem
Data Mining and Knowledge Discovery
Interactive deduplication using active learning
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Robust and efficient fuzzy match for online data cleaning
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
A Primitive Operator for Similarity Joins in Data Cleaning
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Search engine driven author disambiguation
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Collective entity resolution in relational data
ACM Transactions on Knowledge Discovery from Data (TKDD)
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Exploiting web search to generate synonyms for entities
Proceedings of the 18th international conference on World wide web
Swoosh: a generic approach to entity resolution
The VLDB Journal — The International Journal on Very Large Data Bases
Mining document collections to facilitate accurate approximate entity matching
Proceedings of the VLDB Endowment
Evaluation of entity resolution approaches on real-world match problems
Proceedings of the VLDB Endowment
Approximate data instance matching: a survey
Knowledge and Information Systems
Matching unstructured product offers to structured product specifications
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Tailoring entity resolution for matching product offers
Proceedings of the 15th International Conference on Extending Database Technology
A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication
IEEE Transactions on Knowledge and Data Engineering
| Hi-index | 0.00 |
Matching product titles from different data feeds that refer to the same underlying product entity is a key problem in online shopping. This matching problem is challenging because titles across the feeds have diverse representations with some missing important keywords like brand and others containing extraneous keywords related to product specifications. In this paper, we propose a novel unsupervised matching algorithm that leverages web earch engines to (1) enrich product titles by adding important missing tokens that occur frequently in search results, and (2) compute importance scores for tokens based on their ability to retrieve other (enriched title) tokens in search results. Our matching scheme calculates the Cosine similarity between enriched title pairs with tokens weighted by their importance scores. We propose an optimization that exploits the templatized structure of product titles to reduce the number of search queries. In experiments with real-life shopping datasets, we found that our matching algorithm has superior F1 scores compared to IDF-based cosine similarity.