The Revieval of Subject Analysis: A Knowledge-based Approach facilitating Semantic Search

Semantic Search emerged as the new system paradigm in enterprise information systems. However, usually only small amounts of textual enterprise data is semantically prepared for such systems. The manual semantification of these resources typically is a time-consuming process. The automatic semantification requires deep knowledge in Natural Language Processing. Therefore, in this paper we present a novel approach that makes the underlying Subject Indexing task rather a Knowledge Engineering than a Natural Language Processing task. The approach is based on a simple but powerful and intuitive probabilistic model that allows for the easy integration of expert knowledge.