A new technique of determining speaker's intention for sentences in conversation

Authors:
Masao Fuketa;El-Sayed Atlam;Hiro Hanafusa;Kazuhiro Morita;Shinkaku Kashiji;Rokaya Mahmoud;Jun-ichi Aoe
Affiliations:
Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Year:
2005

Citing 8
Cited 0

An Efficient Implementation of Static String Pattern Matching Machines

IEEE Transactions on Software Engineering
An Efficient Digital Search Algorithm by Using a Double-Array Structure

IEEE Transactions on Software Engineering
A document classification method by using field association words

Information Sciences—Informatics and Computer Science: An International Journal
Efficient string matching: an aid to bibliographic search

Communications of the ACM
Introduction to Modern Information Retrieval

Introduction to Modern Information Retrieval
A new method for selecting English field association terms of compound words and its knowledge representation

Information Processing and Management: an International Journal
Text categorization based on k-nearest neighbor approach for web site classification

Information Processing and Management: an International Journal
Documents similarity measurement using field association terms

Information Processing and Management: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Although there are many text classification techniques depending on vector spaces, it is difficult to detect the meaning relating to the user's intention (complaint, encouragement, request, invitation, etc.). The intention to be discussed in this study is very useful for understanding focus points in conversation. This paper presents a technique of determining the speaker's intention for sentences in conversation. The intention association expressions are introduced and the formal rule descriptions with weight using these expressions are defined to build intention classification knowledge. A deterministic multi-attribute pattern-matching algorithm is used to determine the intention class efficiently. From simulation results for 681 E-mail messages of 5,859 sentences, the multi-attribute pattern matching algorithm is about 44.5 times faster than Aho and Corasick method. The precision and recall of intention classification of sentences are 91%, 95%. Precision and recall of the classification of each mail are 88%, 89%.