User adaptive answers generation for conversational agent using genetic programming

Kyoung Min Kim, Sung Soo Lim, Sung-Bae Cho

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Recently, it seems to be interested in the conversational agent as an effective and familiar information provider. Most of conversational agents reply to user's queries based on static answers constructed in advance. Therefore, it cannot respond with flexible answers adjusted to the user, and the stiffness shrinks the usability of conversational agents. In this paper, we propose a method using genetic programming to generate answers adaptive to users. In order to construct answers, Korean grammar structures are defined by BNF (Backus Naur Form), and it generates various grammar structures utilizing genetic programming (GP). We have applied the proposed method to the agent introducing a fashion web site, and certified that it responds more flexibly to user's queries.

Original languageEnglish
Pages (from-to)813-819
Number of pages7
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3177
Publication statusPublished - 2004 Dec 1

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Genetic programming
Genetic Programming
Grammar
Query
Usability
Websites
Stiffness

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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