Name
Title | ||
|---|---|---|
A Case Study on Data Quality, Privacy, and Evaluating the Outcome of Entity Resolution Processes. |
Abstract | ||
|---|---|---|
This paper presents ongoing research conducted through collaboration between the University of Arkansas at Little Rock and the Arkansas Department of Education to develop an entity resolution and identity management system. The process includes a multi-phase approach consisting of data-quality analysis, selection of entity-identity attributes for entity resolution, defined a rule set using the open source entity-resolution system named OYSTER and used entropy approach to identify the potential false positive and false negative. The research is the first known of its kind to evaluate privacy-enhancing, entity-resolution rule sets in a state education agency. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.4018/IJOCI.2016070101 | IJOCI |
Field | DocType | Volume |
Data science,Data mining,Data quality,Name resolution,Computer science,Identity management system,Knowledge management,Benchmarking | Journal | 6 |
Issue | Citations | PageRank |
3 | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pei Wang | 1 | 0 | 0.68 |
| Daniel Pullen | 2 | 0 | 3.04 |
| Fan Liu | 3 | 6 | 3.33 |
| William C. Decker | 4 | 0 | 0.34 |
| Ningning Wu | 5 | 49 | 16.41 |
| John R. Talburt | 6 | 95 | 42.78 |