DocumentCode
145387
Title
Probabilistic Matching Compared to Deterministic Matching for Student Enrollment Records
Author
Pei Wang ; Pullen, Daniel ; Talburt, John R. ; Ningning Wu
Author_Institution
Univ. of Arkansas at Little Rock, Little Rock, AR, USA
fYear
2014
fDate
7-9 April 2014
Firstpage
355
Lastpage
359
Abstract
This paper compares entity resolution results obtained by using both probabilistic and deterministic matching when applied to the deduplication of student enrollment data. The approach outlined in this paper uses deterministic matching to represent equivalence for the calculation of weights to be used in probabilistic matching based on the Fellegi-Sunter model.
Keywords
educational administrative data processing; pattern matching; Fellegi-Sunter model; deterministic matching; entity resolution results; probabilistic matching; student enrollment data; student enrollment records; Complexity theory; Educational institutions; Erbium; Error analysis; Knowledge engineering; Probabilistic logic; Rocks; Boolean Match Rules; Entity Resolution; Scoring Rule; Talburt-Wang Index;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology: New Generations (ITNG), 2014 11th International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4799-3187-3
Type
conf
DOI
10.1109/ITNG.2014.17
Filename
6822223
Link To Document