Information retrieval using deep natural language processing

Abstract

This paper addresses some problems of the conventional information retrieval (IR) systems, by suggesting an approach to information retrieval that uses deep natural language processing (NLP). The proposed client-side IR system employs a Head-Driven Phrase Grammar (HPSG) formalism and uses Attribute Values Matrices (AVMs) for information storage, representation and communication. The paper describes the architecture and the main processes of the system. The initial experimental results following the implementation of the HPSG processor show that the extraction of semantic information using the HPSG formalism is feasible.