Development of An Intelligent NLP-Based Audit Plan Knowledge Discovery System
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 89-97 |
| Journal / Publication | Journal of Emerging Technologies in Accounting |
| Volume | 17 |
| Issue number | 1 |
| Online published | 1 Oct 2019 |
| Publication status | Published - 2020 |
Link(s)
Abstract
Auditors’ discussions in audit plan brainstorming sessions provide valuable knowledge on how audit engagement teams evaluate information, identify and assess risks, and make audit decisions. Collected expertise and experience from experienced auditors can be used as decision support for future audit plan engagements. With the help of Natural Language Processing (NLP) techniques, this paper proposes an intelligent NLP-based audit plan knowledge discovery system (APKDS) that can collect and extract important contents from audit brainstorming discussions and transfer the extracted contents into an audit knowledge base for future use.
Research Area(s)
- audit decision support, spoken content processing, NLP, audit brainstorming sessions
Bibliographic Note
Research Unit(s) information for this publication is provided by the author(s) concerned.
Citation Format(s)
Development of An Intelligent NLP-Based Audit Plan Knowledge Discovery System. / Li, Qiao; Liu, Junming.
In: Journal of Emerging Technologies in Accounting, Vol. 17, No. 1, 2020, p. 89-97.
In: Journal of Emerging Technologies in Accounting, Vol. 17, No. 1, 2020, p. 89-97.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
