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 language | English |
|---|---|
| Pages (from-to) | 813-819 |
| Number of pages | 7 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 3177 |
| Publication status | Published - 2004 Dec 1 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
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User adaptive answers generation for conversational agent using genetic programming. / Kim, Kyoung Min; Lim, Sung Soo; Cho, Sung-Bae.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3177, 01.12.2004, p. 813-819.Research output: Contribution to journal › Article
TY - JOUR
T1 - User adaptive answers generation for conversational agent using genetic programming
AU - Kim, Kyoung Min
AU - Lim, Sung Soo
AU - Cho, Sung-Bae
PY - 2004/12/1
Y1 - 2004/12/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=26944431845&partnerID=8YFLogxK
M3 - Article
VL - 3177
SP - 813
EP - 819
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -