Natural language based heavy personal assistant architecture for information retrieval and presentation

Abstract

In this paper we present the progress of the natural language usage as the paradigm for information extraction and presentation in the enterprise environment. Distributed heavy personal assistant architecture and its implementation is presented as the solution to overcome difficulties related of the natural language use in the information systems development. A new methodology based on connectionist and symbol processing techniques for a knowledge worker to process his documents and utterance is suggested. Then we suggest the results from those processes to reuse for new documents classification and generation of small atomic applications. Finally the experiment is presented. We compare Microsoft EQ, IBM WebSphere Voice Server NLU toolbox and our solution for concepts identification accuracy.