Content-Based Support for Annotating New Content in a Wiki for Shape Memory Technology

The application of new technologies such as Shape Memory Technology (SMT) is a challenging task for product developers. On the one hand, product developers have to be aware of this new technology and its potential uses. On the other hand, they have to be enabled to apply SMT in their products. Therefore, the Special Research Field SFB459 – Shape Memory Technology provides a considerable amount of its scientific results in a wiki-based system. This system is accessible online to interested product developers. Comprehensive information about basic material research as well as about the application of SMT is available in the system. However, the usability of this information is limited especially by the complex hierarchical structure of the content, which is due to the different knowledge levels and disciplines of the users. To solve these problems, a new approach has been developed to improve the usability of the wiki and of the information provided. This approach replaces the hierarchical structure by a non-hierarchical collection of articles, which have been connected and rendered accessible by a set of annotations. These annotations allow the application of different methods for inserting and retrieving information. The users are supported by an assistance system which provides methods for the semi-automatic annotation of articles. This system recommends possible annotations using different content-based approaches to text analysis. The evaluation and application of different content-based approaches to a domain-specific wiki for SMT with a comparatively small number of articles is focused in this paper.