  Named entities have been considered and combined with keywords to enhance
information retrieval performance. However, there is not yet a formal and
complete model that takes into account entity names, classes, and identifiers
together. Our work explores various adaptations of the traditional Vector Space
Model that combine different ontological features with keywords, and in
different ways. It shows better performance of the proposed models as compared
to the keyword-based Lucene, and their advantages for both text retrieval and
representation of documents and queries.
