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Daniel L. Pullen
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2010 – 2019
- 2019
- [c8]Pei Wang, Daniel L. Pullen, Maryam Y. Garza, Anita Walden, Meredith N. Zozus:
Data Profiling in Support of Entity Resolution of Multi-Institutional EHR Data. ITCH 2019: 479-483 - [p1]John R. Talburt, Daniel L. Pullen, Melody L. Penning:
Evaluating and Improving Data Fusion Accuracy. Information Quality in Information Fusion and Decision Making 2019: 295-326 - 2017
- [c7]Pei Wang, Daniel L. Pullen, John R. Talburt:
Comparison of Pre-and Post-Resolution Blocking Strategies for Entity Resolution in a Distributed Computing Environment. AMCIS 2017 - [c6]Pei Wang, Daniel L. Pullen, Maryam Y. Garza, Meredith N. Zozus:
The Challenges of, and Why You Should Reconsider Using, Truth Sets for Optimizing Entity Resolution: A Case Study. ICIQ 2017 - 2016
- [j1]Pei Wang, Daniel L. Pullen, Fan Liu, William C. Decker, Ningning Wu, John R. Talburt:
A Case Study on Data Quality, Privacy, and Evaluating the Outcome of Entity Resolution Processes. Int. J. Organ. Collect. Intell. 6(3): 1-20 (2016) - 2015
- [c5]Cheng Chen, Daniel L. Pullen, Reed H. Petty, John R. Talburt:
Methodology for Large-Scale Entity Resolution without Pairwise Matching. ICDM Workshops 2015: 204-210 - [c4]Cheng Chen, Daniel L. Pullen, John R. Talburt:
A visualization system to support clerical review, correction, and confirmation assertions in entity identity information management. ICIQ 2015 - 2014
- [c3]Pei Wang, Daniel L. Pullen, John R. Talburt, Ningning Wu:
Iterative Approach to Weight Calculation in Probabilistic Entity Resolution. ICIQ 2014 - [c2]Pei Wang, Daniel L. Pullen, John R. Talburt, Ningning Wu:
Probabilistic Matching Compared to Deterministic Matching for Student Enrollment Records. ITNG 2014: 355-359 - 2013
- [c1]Daniel L. Pullen, Pei Wang, John R. Talburt, Ningning Wu:
A false positive review indicator for entity resolution systems using Boolean rules. ICIQ 2013
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