Stefan Fleischer

The Legal Perspective on Business to Government Reporting -- A Conceptual Modeling Approach and Its Application in the Financial Sector

Business to Government (BtG) Reporting is a much-regarded research field, even more so since the collapse of the world economy. The topic attracts heightened attention from many financial service companies because they are forced to comply with an increasing number of reporting regulations. In particular, methods to design compliant BtG reporting systems are currently considered inadequate in IS research. This paper presents a way of supporting the management of legal reporting requirements by developing an approach for modeling and analyzing reporting regulations focused on the financial sector. The method is characterized in particular by the ability to represent and analyze legal reporting requirements. Using the examples of Risk Reports and the European Markets in Financial Instruments Directive (MiFID), the modeling and analysis capabilities of the method will be evaluated.

Segmentation of Very Low Resolution Screen-Rendered Text

The lower the resolution of a given text is, the more difficult it becomes to segment it into single characters. The resolution of screen-rendered text can be very low. This paper focuses on smoothed screen-rendered text of very low resolution with typical x-heights of 4 to 7 pixels which is much lower than in other low resolution OCR situations. We propose a recognition-based segmentation algorithm which makes use of over segmentation by dynamic programming, candidate rating by single character classifiers and a graph based search algorithm for an optimal cut sequence. The algorithm is described in detail and experimental results are presented which show the performance on example screen- shot images taken from the public Screen-Word database.

A multiple classifier approach for the recognition of screen-rendered text

The lower the resolution of a given text is, the more difficult it becomes to segment and to recognize it. The resolution of screen-rendered text can be very low. With a typical x-height of 4 to 7 pixels it is much lower as in other low resolution OCR situations. Modern OCR approaches for such very low resolution text use a classification-based segmentation where the underlying classifier plays an important role. This paper presents a multiple classifier system for the classification of single characters. This system is used as a subsystem for the classification-based segmentation within a system to read screen-rendered text. The paper shows that the presented multiple classifier system outperforms the best former single classifier system on single characters by far and it shows the impact of using the multiple classifier system on the word reading performance.

Conceptual Modeling of Electronic Content and Documents in ECM Systems Design: Results from a Modeling Project at Hoval

The implementation of enterprise content management (ECM) software requires careful analysis of an organization’s content and document assets, and conceptual information models can provide substantial input for ECM systems design. In particular, content models can support the documentation of both organizational and technological conditions and can illuminate software-related requirements. Therefore, a conceptual modeling language for electronic content and documents has to meet several conditions: It should facilitate description of how content can be reused in different documents, the creators and users of content, and the software systems involved. In addition, given the vast number of digital assets created and used in today’s organizations, such a language has to safeguard a clear and consistent representation while also being ready for efficient adaptation and maintenance. With the help of the general criteria of conceptual modeling proposed by Becker et al. (e.g., correctness, relevance, clarity), this chapter identifies these and related requirements and argues that they are not sufficiently met by existing modeling approaches. As a response, we propose a novel modeling language that we developed and evaluated during the course of a modeling project at Hoval, to be used in describing electronic content and documents.