Development and Evaluation of a Prototype web XBRL-Enabled Financial Platform for the Generation and Presentation of Financial Statements according to IFRS

Stergiaki, Elissavet; Vazakidis, Athanasios; Stavropoulos, Antonios

doi:10.15640/ijat.v3n1a5

Cited by 5 publications

(6 citation statements)

References 33 publications

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“…e evolution of the business concept needs to be supported by massive data on the one hand, and various data technologies to complete the processing of the data to extract the core from data of subscribers on the other. erefore, the urgent issues that broadcasters need to solve at this stage are the integration of massive internal and external data, the modeling of intelligent user graphs, and the use of deep machine learning for user prediction [5].…”

Section: Introductionmentioning

confidence: 99%

Research on Application Effective Evaluation of Artificial Intelligence Technology in Marketing Communication

Yang

2022

Security and Communication Networks

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In order to solve the current problems of ignoring individual user differences, rising marketing costs, and customer churn in the crude marketing process, we combine deep machine learning technology and the long-term operational experience of Media Network Co. deep learning. By extracting features from the network data in image format, DNSI can obtain three kinds of neighbor structure influence. The optimal graph theory approach is used to construct user intelligence graphs, and then deep machine learning techniques are used to achieve accurate marketing in combination with different scenarios. Experimental results on several real-world network data sets for tasks such as node attribute prediction, category centrality measure, and user behavior prediction show the superiority of the model in most cases.

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Section: Introductionmentioning

confidence: 99%

Research on Application Effective Evaluation of Artificial Intelligence Technology in Marketing Communication

Yang

2022

Security and Communication Networks

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“…How to realize accurate education according to students' abilities has indeed become a difficult problem for mass higher education at this stage. e emergence of big data in education provides an opportunity for universities to realize personalized student management [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Construction of College Students’ Growth and Development Index System Based on Data Association Mining and Deep Learning Model

Mao

2021

Security and Communication Networks

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The rise of big data in the field of education provides an opportunity to solve college students’ growth and development. The establishment of a personalized student management mode based on big data in universities will promote the change of personalized student management from the empirical mode to the scientific mode, from passive response to active warning, from reliance on point data to holistic data, and thus improve the efficiency and quality of personalized student management. In this paper, using the latest ideas and techniques in deep learning such as self-supervised learning and multitask learning, we propose an open-source educational big data pretrained language model F-BERT based on the BERT model architecture. Based on the BERT architecture, F-BERT can effectively and automatically extract knowledge from educational big data and memorize it in the model without modifying the model structure specific to educational big data tasks so that it can be directly applied to various educational big data domain tasks downstream. The experiment demonstrates that Vanilla F-BERT outperformed the two Vanilla BERT-based models, Vanilla BERT and BERT tasks, by 0.0.6 and 0.03 percent, respectively, in terms of accuracy.

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“…Other research related to the discussion and evaluation of the development of "XBRL-Passport" (Pilot Athens stock exchange's Statements Source Portal). This prototype was built as a smart solution for clients, because of the long process and various formats of collecting and analyzing financial data from various sources, thus making companies have to spend more consistency costs, see [18]. The prototype architecture consists of 3 simple layers, namely: the database layer with MySQL, the logic layer with PHP, and the application layer using the web.…”

Section: Literature Reviewmentioning

confidence: 99%

The Financial Services Authority of Indonesia E-Reporting System Development Based on Metadata XBRL Taxonomy

Farizd¹,

Suharjito²

2020

Adv. sci. technol. eng. syst. j.

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The XBRL taxonomy has been proven to be able to restore various forms of redundancies and ambiguities in making financial reports from financial service institutions. However, the nature of XBRL which is oriented towards documents and based on XML makes the XBRL taxonomy difficult to use because the information cannot be directly read by ordinary users. The same obstacle was felt by the Financial Services Authority of Indonesia (Indonesian: Otoritas Jasa Keuangan or OJK) as financial regulator in utilizing the XBRL taxonomy, therefore a web-based application system called E-Reporting was developed to input financial statements conducted from financial service institutions to the regulator. The core of the application system is the XBRL taxonomy reading and mapping function, utilizing the Java library for reading XML and the Spring Java framework as a system backend, the Zkoss framework as the system frontend, and the database for storing data and specifically developed for the needs of the OJK. The purpose of this paper is to show other ways of implementing XBRL taxonomy, one of which is to present XBRL into a dynamic user interface according to the dynamic and flexible nature of XBRL. The results of the system evaluation indicate that the system is quite good at presenting the taxonomy into a user interface that suits the needs and can ease the burden of data validation, as well as providing convenience in forming the instance document, which is needed as the final result of the reporting process carried out by financial service institutions. Therefore, this system has been proven to provide added value in the use of XBRL taxonomy in financial reporting activities.

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Development and Evaluation of a Prototype web XBRL-Enabled Financial Platform for the Generation and Presentation of Financial Statements according to IFRS

Cited by 5 publications

References 33 publications

Research on Application Effective Evaluation of Artificial Intelligence Technology in Marketing Communication

Research on Application Effective Evaluation of Artificial Intelligence Technology in Marketing Communication

Evaluation and Construction of College Students’ Growth and Development Index System Based on Data Association Mining and Deep Learning Model

The Financial Services Authority of Indonesia E-Reporting System Development Based on Metadata XBRL Taxonomy

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