Financial Analysis System using XBRL and the Interaction Support

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  • ＸＢＲＬを利用した財務分析システムとそのインタラクション支援
  • XBRL オ リヨウ シタ ザイム ブンセキ システム ト ソノ インタラクション シエン

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Abstract

An existing financial analysis system doesn't consider user's characteristic, and not be a system that considered the interaction between systems as the user though there are a lot of researches that do the risk and the analysis of the affairs of a business on the enterprise in the financial analysis. There is an analysis angle of financial analysis angle in the financial analysis, and the financial analysis is done generally based on it. The one from here from everything are in information that can be read there even if the financial data that the user demands is decided various the one, and obtained by noticing the person who does the financial analysis though the financial analysis seems to have a specific purpose from the beginning. That is, it can be said that it has the side of exploratory data analysis. The user has it in exploratory data analysis through the search process for this case, the user will have it a lot of actualizing an own information request gradually by repeating the interaction and make to exquisite as for the possibility that the information demand is understood an own information request, and changes gradually and changes in quality during the search. Then, the system that supports the user interaction in the financial analysis support system and the financial analysis support system of the Web base using XBRL is constructed in the present study. The interaction design named Model+Others was proposed, and mounted according to three financial analysis angles. These Model+Others related to the importance in the financial analysis angle, divided a financial index from the relation of the index into three hierarchies, assumed “Model”, and located other parts to “Others”. It is thought that the interaction support is enabled by applying these models. It is time when did not apply in case of occasioned to apply the user model, and user's use log was pursued and analyzed from an ethno viewpoint in detail the verification your what influence being exerted on the use user. The interaction support was done by having used proposed “Model+Others”, and as a result, it was noticed the change in user's demand information, and was able to observe each user's feature interaction result.

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