Soft computing techniques for querying XBRL data

• Autores: Marek Reformat, Ronald R. Yager
• Localización: Intelligent systems in accounting, finance & management, ISSN-e 1099-1174, Vol. 22, Nº. 3, 2015, págs. 179-199
• Idioma: inglés
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• Resumen

  • Availability of business data is an important aspect of effective financial activities. An easy access to financial information has immense influence on actions and decisions regarding investing, trade and operations of companies and firms. The proposed standard – eXtensible Business Reporting Language (XBRL) – provides a means to create a uniform framework for representing corporate and financial information. XBRL defines an easily interpretable, machine-readable and XML-based data format. Its flexibility allows for representing business data using different languages, as well as following different regulation standards.

    One of important benefits of XBRL is application of XML-based tools and systems that enable easy preparation, processing and validation of corporate data. It is also possible to use XML-based storage and query systems.

    In this paper we propose and describe a concept of soft queries. They provide the users with a human-friendly interface for interacting with XBRL data. These queries are equipped with linguistic terms (such as large, medium, small) and linguistic qualifiers (all, mostly). Such queries are able to provide the users with results similar to the results obtained when they analyse data themselves. Linguistic terms and qualifiers are represented as fuzzy sets. Fuzzy-based operations and aggregation operators allow for mimicking a human-like processing of data. The proposed approach is illustrated with queries executed on an XBRL document