NDLI: Probabilistic estimates of attribute statistics and match likelihood for people entity resolution

Content Provider	IEEE Xplore Digital Library
Author	Xin Wang Ang Sun Kardes, H. Agrawal, S. Lin Chen Borthwick, A.
Copyright Year	2014
Description	Author affiliation: Data Res., Intelius Inc., Bellevue, WA, USA (Xin Wang; Ang Sun; Kardes, H.; Agrawal, S.; Lin Chen; Borthwick, A.)
Abstract	For big data practitioners, data integration/entity resolution/record linkage is one of the key challenges we face from day to day. Entity resolution/record linkage with high precision and recall on a large graph with billions of nodes, and hundreds of times more edges poses significant scalability challenges. Similarity based graph partition is still the most scalable method available. This paper presents a probabilistic method to approximate the match likelihood of a pair of records by incorporating values of different attributes and their aggregates/statistics. The quality of the approximates depend on the accuracy of the estimates of the aggregated values. The paper adapts the GTM model described in [1] to obtain the estimates. We present experimental results based on real world commercial data sources to show that the estimates obtained via GTM model is better than the baseline. Our experimental results also showed that the approximate match likelihood can improve the recall of the similarity function.
Starting Page	92
Ending Page	99
File Size	1117723
Page Count	8
File Format	PDF
ISBN	9781479956661
DOI	10.1109/BigData.2014.7004459
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Couplings Entity Resolution Adaptation models Data Fusion Record Linkage Big Data Demographic Information Sociology Clustering algorithms Cities and towns Frequency estimation Approximate Probabilistic Estimates Data Integration
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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