User adaptive answers generation for conversational agent using genetic programming

Kyoung Min Kim, Sung Soo Lim, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingChapter

5 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
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsZheng Rong Yang, Richard Everson, Hujun Yin
PublisherSpringer Verlag
Pages813-819
Number of pages7
ISBN (Print)3540228810, 9783540228813
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3177
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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