Query based intelligent web interaction with real world knowledge

This paper describes an integrated system based on open-domain and domain-specific knowledge for the purpose of providing query-based intelligent web interaction. It is understood that general purpose conversational agents are not able to answer questions on specific domain subject. On the other han...

Full description

Saved in:
Bibliographic Details
Main Authors: Goh, Ong Sing, Fung, C.C., Wong, K.W.
Format: Article
Language:English
English
Published: Ohmsha, Ltd. 2007
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/12386/1/Query_Based_Intelligent_Web_Interaction_with_Real_World_Knowledge_-page_1-3_.pdf
http://eprints.utem.edu.my/id/eprint/12386/2/Query_Based_Intelligent_Web_Interaction_with_Real_World_Knowledge_-page_1_.pdf
http://eprints.utem.edu.my/id/eprint/12386/
http://researchrepository.murdoch.edu.au/558/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknikal Malaysia Melaka
Language: English
English
Description
Summary:This paper describes an integrated system based on open-domain and domain-specific knowledge for the purpose of providing query-based intelligent web interaction. It is understood that general purpose conversational agents are not able to answer questions on specific domain subject. On the other hand, domain specific systems lack the flexibility to handle common sense questions. To overcome the above limitations, this paper proposed an integrated system comprises of an artificial intelligent conversation software robot or chatterbot, called Artificial Intelligence Natural-language Identity (hereafter, AINI), and an Automated Knowledge Extraction Agent (AKEA) for the acquisition of real world knowledge from the Internet. The objective of AKEA is to retrieve real world knowledge or information from trustworthy websites. AINI is the mechanism used to manage the knowledge and to provide appropriate answer to the user. In this paper, we compare the performance of the proposed system against two popular search engines, two question answering systems and two other conversational systems.