The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Application of Text Mining Methodologies to Health Insurance Schedules
|
Author(s): Ah Chung Tsoi (Monash University, Australia), Phuong Kim To (Tedis P/L, Australia)and Markus Hagenbuchner (University of Wollongong, Australia)
Copyright: 2009
Pages: 22
Source title:
Handbook of Research on Text and Web Mining Technologies
Source Author(s)/Editor(s): Min Song (New Jersey Institute of Technology, USA)and Yi-Fang Brook Wu (New Jersey Institute of Technology, USA)
DOI: 10.4018/978-1-59904-990-8.ch045
Purchase
|
Abstract
This chapter describes the application of a number of text mining techniques to discover patterns in the health insurance schedule with an aim to uncover any inconsistency or ambiguity in the schedule. In particular, we will apply first a simple “bag of words” technique to study the text data, and to evaluate the hypothesis: Is there any inconsistency in the text description of the medical procedures used? It is found that the hypothesis is not valid, and hence the investigation is continued on how best to cluster the text. This work would have significance to health insurers to assist them to differentiate descriptions of the medical procedures. Secondly, it would also assist the health insurer to describe medical procedures in an unambiguous manner.
Related Content
.
© 2023.
34 pages.
|
.
© 2023.
15 pages.
|
.
© 2023.
15 pages.
|
.
© 2023.
18 pages.
|
.
© 2023.
24 pages.
|
.
© 2023.
32 pages.
|
.
© 2023.
21 pages.
|
|
|