A multilevel natural language query approach conversational agent systems

The main aim of this research is to investigate a novel technique for implementing a conversational intelligent agent system on the web. The research will focus on a multilevel natural language query approach. While the present World Wide Web provides a distributed hypermedia interface to the vast amount of information on the Internet, there is a lack of appropriate metadata to that content. Instead of being a giant library as intended, increasing sections of the Web resemble a giant garbage dump. A multilevel natural language query system is described in this paper for the representation of knowledge in specific and open domains. The six-layer conversational agent system includes Spellcheck, Natural Language Understanding and Reasoning, FAQChat, Metadata Index Search, Pattern Matching and Case-Based Reasoning, and Supervised Learning. This technique is demonstrated using extracts from queries on the field of data relating to the Bird Flu H5N1 pandemic crisis.