ASAE at STI Innsbruck coordinates the MUSING project participation (see projects -- MUSING), leads several follow-ups to the former DERI Business Development project, and participates in the SHAPE project (see projects -- SHAPE). The DERI Business Development project finished successfully at the end of 2007. The current follow-ups to the business development project are
  • GoldenBullet (GB), an intelligent text-based classifier for products and services. GB learns classification based on textual product or service descriptions. The open architecture of GB will allow it to target learning to different product and services classification standards like UNSPSC, e-Class, EAN and others. GB is based on a Bayesian classifier engine and several natural language processing modules. The open taxonomy interface is implemented using JAX-R.
  • Industry days focussing the future of business reporting languages. With the increasing adoption of XBRL (extensible business reporting language) and increasing legal regulation of reporting, companies and public bodies face many challenges. Among these, the compliance of internal reporting data structures and procedures with legislatory regulations is most prominent. The aim of our industry days is to discuss recent developments of business reporting languages and tools relevant to the compliance management needed with a particular focus on Tyrolian industry.

Golden Bullet


GoldenBullet is a semi-automatic product classification system.

Product classification for warehouse catalogues is a labour-intensive, complicated, time-consuming and error-prone process that requires tremendous efforts. In frequent repeated cycles, millions of millions of products have to be classified with regard to multiple existing standards (e.g. UNSPSC, GPC, e-Class) Furthermore, each of these standards may contain several thousands of target classes or customer specific taxonomies.

In the project GoldenBullet we aim to realize an innovative semi-automatic workflow to be delivered as service with a 95% classification accuracy via an integrated web application. This workflow seamlessly combines a fully automated product classifier with accurate manual classification and a background learning process. Further industrial cooperation will be fostered by applying industry scenarios to the workflow.

If you are intresting in Golden Bullet, please visit the project web page or contact us. Golden Bullet is managed by Christian Leibold




MUSING aims at developing a new generation of Business Intelligence (BI) tools and modules founded on semantic-based knowledge and content systems. MUSING will integrate Semantic Web and Human Language technologies and combine declarative rule-based methods and statistical approaches for enhancing the technological foundations of knowledge aquisition and reasoning in BI applications. The breakthrough impact of MUSING on semantic-based BI will be measured in three streategic, vertical domains: Finance, through development and vcalidation of next generation (Basel II and beyond) semantic-based BI solutions, with particular reference to Credit Risk MAnagement; Internationalisation, through development and validation of next generation semantic-based internatiojnalisation platforms; Operational Risk Management, through development and validation of semantic-driven knowledge systems for measurement and mitigation tools, with particular reference to IT operational risks faced by IT-intensive organisations.

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