Abstract

Building a knowledge base (KB) describing domain-specific entities is an important problem in industry, examples including KBs built over companies (e.g. Dun & Bradstreet), skills (LinkedIn, CareerBuilder) and people (inome). The task involves several engineering challenges, including devising effective procedures for data extraction, aggregation and deduplication. Data extraction involves processing multiple information sources in order to extract domain-specific data instances. The extracted instances must be aggregated and deduplicated; that is, instances referring to the same underlying entity must be identified and merged. This paper describes a pipeline developed at CareerBuilder LLC for building a KB describing employers, by first extracting entities from both global, publicly available data sources (Wikipedia and Freebase) and a proprietary source (Infogroup), and then deduplicating the instances to …

Date

October 29, 2015

Authors

Mayank Kejriwal, Qiaoling Liu, Ferosh Jacob, Faizan Javed

Conference

2015 IEEE International Conference on Big Data (Big Data)

Pages

1144-1153

Publisher

IEEE