Technology classification with latent semantic indexing

Many national and international governments establish organizations for applied science research funding. For this, several organizations have defined procedures for identifying relevant projects that based on prioritized technologies. Even for applied science research projects, which combine several technologies it is difficult to identify all corresponding technologies of all research-funding organizations. In this paper, we present an approach to support researchers and to support research-funding planners by classifying applied science research projects according to corresponding technologies of research-funding organizations. In contrast to related work, this problem is solved by considering results from literature concerning the application based technological relationships and by creating a new approach that is based on latent semantic indexing (LSI) as semantic text classification algorithm. Technologies that occur together in the process of creating an application are grouped in classes, semantic textual patterns are identified as representative for each class, and projects are assigned to one of these classes. This enables the assignment of each project to all technologies semantically grouped by use of LSI. This approach is evaluated using the example of defense and security based technological research. This is because the growing importance of this application field leads to an increasing number of research projects and to the appearance of many new technologies.

► Use latent semantic indexing to identify semantic textual patterns in technology descriptions. ► Automated identification of application based technological relationships. ► Assign project descriptions to these related technologies. ► Support researcher and research-funding planners by their classification decision.