Mobile applications have to adhere to many constraints. Contexteng.ne has been developed for the Android platform to easier deal with such limitations and situation-specific information across applications to, thus, c...
smart FIX is a product portfolio for knowledge based extraction of data from any document format. The system automatically determines the document type and extracts all relevant data for the respective business proces...
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smartFIX is a product portfolio for knowledge based extraction of data from any document format. The system automatically determines the document type and extracts all relevant data for the respective business process...
详细信息
smartFIX is a product portfolio for knowledge based extraction of data from any document format. The system automatically determines the document type and extracts all relevant data for the respective business process. Data that is unreliably recognized is forwarded to a verification workplace for manual checking. In general, users have no difficulties to interpret the document data and wonder why the system needs additional input. For that reason, we implemented an explanation component that is used to justify extraction results, thus, increasing confidence of users. The component is using a semantic log making it possible to provide understandable explanations. We illustrate the benefits of that kind of technology in contrast to the current smartFIX Log Viewer by means of a preliminary user experiment.
explanation, trust, and transparency are concepts that are strongly tied in with users' confidence in, and acceptance of computerised systems. Case-based reasoning (CBR) systems lend themselves easily to generate ...
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explanation, trust, and transparency are concepts that are strongly tied in with users' confidence in, and acceptance of computerised systems. Case-based reasoning (CBR) systems lend themselves easily to generate explanations, as they typically organise and represent knowledge in a way that makes it possible to reason about and thereby generate explanations. The work presented here is a first step towards making a CBR eng.ne explanation-aware. We demonstrate how a plugin for Protégé and myCBR can facilitate explanations for the retrieval phase of a CBR system.
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