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

A Generalized Vector Space Model for Ontology-Based Information Retrieval