  Named entities (NE) are objects that are referred to by names such as people,
organizations and locations. Named entities and keywords are important to the
meaning of a document. We propose a generalized vector space model that
combines named entities and keywords. In the model, we take into account
different ontological features of named entities, namely, aliases, classes and
identifiers. Moreover, we use entity classes to represent the latent
information of interrogative words in Wh-queries, which are ignored in
traditional keyword-based searching. We have implemented and tested the
proposed model on a TREC dataset, as presented and discussed in the paper.
