Abstract
Due to formatting differences, the difficulties of processing the textual disclosures and integrating them with quantitative financial data are well documented in the literature. Using a design science methodology, this paper describes a method that automatically extracts relevant textual data from annual reports published in Chinese. These extracted words are then mapped to a knowledge framework we proposed. This paper shows that it is technologically feasible to reorganize the MD&A contents into any given knowledge structure to improve the search capability, readability, and cohesiveness of the MD&A contents. Finally, we demonstrate a prototype system that uses semantic web technology to achieve information integration that presents XBRL formatted accounting data with relevant textual disclosures together to assist user decision making.
Original language | American English |
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Journal | International Journal of Accounting Information Systems |
Volume | 21 |
DOIs | |
State | Published - Jun 2016 |
Keywords
- Business information retrieval
- Integration of financial and non-financial information
- Text analytics
- XBRL
Disciplines
- Computer Sciences
- Library and Information Science