Using the Relational Model and Part-of-Speech Tagging to Implement Text Relevance

We introduce a database design that improves prior work on document retrieval within the relational model. While previous approaches require extensions to the relational model, our approach uses an unchanged relational system. We focus on the implementation of assigning a measure of relevance between a query and a document as this is more useful for large document databases. Since run-time performance is critical to interactive document retrieval applications, we provide a detailed performance analysis of the number of disk reads required by our approach as compared to a traditional IR system. Additionally, we show how an existing stochastic heuristic which assigns the parts of speech to a document can be incorporated into the relational model. 1 Introduction The idea of using relational systems to facilitate text processing was first proposed in [9]. In this work it was shown that simplistic keyword searches can be done using unchanged SEQUEL (a precursor to SQL). Additional operatio..