Abstract
Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.
| Original language | English |
|---|---|
| Title of host publication | TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 178-185 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781509057320 |
| DOIs | |
| Publication status | Published - 2017 Mar 16 |
| Event | 2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 - Hsinchu, Taiwan Duration: 2016 Nov 25 → 2016 Nov 27 |
Publication series
| Name | TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings |
|---|
Other
| Other | 2016 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2016 |
|---|---|
| Country | Taiwan |
| City | Hsinchu |
| Period | 16-11-25 → 16-11-27 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Control and Optimization
- Information Systems
Cite this
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Topic suggestion by Bayesian network enhanced tag inference in community question answering. / Tumenbayar, Gerel; Kao, Hung-Yu.
TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 178-185 7880110 (TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Topic suggestion by Bayesian network enhanced tag inference in community question answering
AU - Tumenbayar, Gerel
AU - Kao, Hung-Yu
PY - 2017/3/16
Y1 - 2017/3/16
N2 - Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.
AB - Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.
UR - http://www.scopus.com/inward/record.url?scp=85017623424&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85017623424&partnerID=8YFLogxK
U2 - 10.1109/TAAI.2016.7880110
DO - 10.1109/TAAI.2016.7880110
M3 - Conference contribution
AN - SCOPUS:85017623424
T3 - TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings
SP - 178
EP - 185
BT - TAAI 2016 - 2016 Conference on Technologies and Applications of Artificial Intelligence, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -