@inproceedings{ca6eff680d1843f2aaaa0644808b733f,
title = "An approach for intention perception based on knowledge network",
abstract = "Intention perception is an enormous challenge for intelligent system in a short conversation. This paper introduces an approach for intention perception based on knowledge network during human-computer interaction. The entity knowledge network is build using the incidence relation between entity and attribute words. Entity and attributed words are extracted from massive crawled topic contents. The intention of user is identified using an atlas walk algorithm based on the keywords of user input. Experiment results show that the proposed algorithm based on knowledge network precept user's intent more precisely.",
keywords = "Conversation System, Graph Path, Intention Perception, Knowledge network, Web Intelligence",
author = "Huakang Li and Guozi Sun and Bei Xu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 10th International Conference on Semantics, Knowledge and Grids, SKG 2014 ; Conference date: 27-08-2014 Through 29-08-2014",
year = "2014",
month = nov,
day = "20",
doi = "10.1109/SKG.2014.23",
language = "English",
series = "Proceedings - 2014 10th International Conference on Semantics, Knowledge and Grids, SKG 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "133--136",
editor = "Hai Zhuge and Xiaoping Sun",
booktitle = "Proceedings - 2014 10th International Conference on Semantics, Knowledge and Grids, SKG 2014",
}