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2017
Journal Article
Title
Contextualization and Recommendation of Annotations to Enhance Information Exchange in Assembly Assistance
Abstract
Increasingly flexible production processes require intelligent assistance systems containing information and knowledge to maintain high quality and efficiency. To ensure a reliable supply of information, it is of great importance to find easy and fast ways to record and store "new" information, as well as to provide a sensible mechanism to supply the information when needed. In this paper an approach is presented that uses annotations in combination with a formalized knowledge base that represents the work domain. This pre-condition enables a context-based annotation recommendation. A framework is proposed to integrate different factors to measure the relevance of an annotation according to a given situation. The approach is illustrated using the example of an assembly assistance system. To evaluate the users' attitude regarding annotations as instruction support and to test the system's capabilities when handling a great number of annotations some studies were performed and analyzed.