Abstract
As access to information becomes more intensive in society, a great deal of that information is becoming available through diverse channels. Accordingly, users require effective methods for accessing this information. Conversational agents can act as effective and familiar user interfaces. Although conversational agents can analyze the queries of users based on a static process, they cannot manage expressions that are more complex. In this paper, we propose a system that uses semantic Bayesian networks to infer the intentions of the user based on Bayesian networks and their semantic information. Since conversation often contains ambiguous expressions, the managing of context and uncertainty is necessary to support flexible conversational agents. The proposed method uses mixed-initiative interaction (MII) to obtain missing information and clarify spurious concepts in order to understand the intention of users correctly. We applied this to an information retrieval service for websites to verify the usefulness of the proposed method.
| Original language | English |
|---|---|
| Pages (from-to) | 225-236 |
| Number of pages | 12 |
| Journal | Information Processing and Management |
| Volume | 43 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2007 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Information Systems
- Media Technology
- Computer Science Applications
- Management Science and Operations Research
- Library and Information Sciences
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A semantic Bayesian network approach to retrieving information with intelligent conversational agents. / Kim, Kyoung Min; Hong, Jin Hyuk; Cho, Sung-Bae.
In: Information Processing and Management, Vol. 43, No. 1, 01.01.2007, p. 225-236.Research output: Contribution to journal › Article
TY - JOUR
T1 - A semantic Bayesian network approach to retrieving information with intelligent conversational agents
AU - Kim, Kyoung Min
AU - Hong, Jin Hyuk
AU - Cho, Sung-Bae
PY - 2007/1/1
Y1 - 2007/1/1
N2 - As access to information becomes more intensive in society, a great deal of that information is becoming available through diverse channels. Accordingly, users require effective methods for accessing this information. Conversational agents can act as effective and familiar user interfaces. Although conversational agents can analyze the queries of users based on a static process, they cannot manage expressions that are more complex. In this paper, we propose a system that uses semantic Bayesian networks to infer the intentions of the user based on Bayesian networks and their semantic information. Since conversation often contains ambiguous expressions, the managing of context and uncertainty is necessary to support flexible conversational agents. The proposed method uses mixed-initiative interaction (MII) to obtain missing information and clarify spurious concepts in order to understand the intention of users correctly. We applied this to an information retrieval service for websites to verify the usefulness of the proposed method.
AB - As access to information becomes more intensive in society, a great deal of that information is becoming available through diverse channels. Accordingly, users require effective methods for accessing this information. Conversational agents can act as effective and familiar user interfaces. Although conversational agents can analyze the queries of users based on a static process, they cannot manage expressions that are more complex. In this paper, we propose a system that uses semantic Bayesian networks to infer the intentions of the user based on Bayesian networks and their semantic information. Since conversation often contains ambiguous expressions, the managing of context and uncertainty is necessary to support flexible conversational agents. The proposed method uses mixed-initiative interaction (MII) to obtain missing information and clarify spurious concepts in order to understand the intention of users correctly. We applied this to an information retrieval service for websites to verify the usefulness of the proposed method.
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UR - http://www.scopus.com/inward/citedby.url?scp=33748289948&partnerID=8YFLogxK
U2 - 10.1016/j.ipm.2006.04.001
DO - 10.1016/j.ipm.2006.04.001
M3 - Article
VL - 43
SP - 225
EP - 236
JO - Information Processing and Management
JF - Information Processing and Management
SN - 0306-4573
IS - 1
ER -