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2012 IEEE 12th International Conference on Data Mining Workshops
An Ensemble-Based Named Entity Recognition Solution for Detecting Consumer Products
Brussels, Belgium Belgium
December 10-December 10
ISBN: 978-1-4673-5164-5
This paper presents a technical description of a solution for International Conference on Data Mining 2012 Contest -- Consumer Products number 1. The Contest provided a dataset including thousands of text items, a product catalog with over fifteen million products, and hundreds of manually annotated product mentions to support data-driven approaches. The task was to identify product mentions within a large user-generated web-based textual corpus and disambiguate the mentions against the large product catalog. The solution consists of an ensemble-based algorithm for processing a textual content. It uses Conditional Random Fields and a special approach which recognizes product mentions. This solution finished in the third place in the contest.
Index Terms:
Catalogs,Consumer products,Lead,Algorithm design and analysis,Conferences,Training data,Prediction algorithms,ICDM Contest,Conditional Random Field,Sequence Tagging,Consumer products,Named Entity Recognition
Citation:
Lukasz Romaszko, "An Ensemble-Based Named Entity Recognition Solution for Detecting Consumer Products," icdmw, pp.865-868, 2012 IEEE 12th International Conference on Data Mining Workshops, 2012
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