Title :
An Approach for Intention Perception Based on Knowledge Network
Author :
Huakang Li ; Guozi Sun ; Bei Xu
Author_Institution :
Dept. of Comput. Sci. & Technol., Nanjing Univ. of Posts & Telecommun., Nanjing, China
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 :
human computer interaction; knowledge based systems; entity knowledge network; human-computer interaction; intelligent system; intention perception; Databases; Diseases; Knowledge based systems; Knowledge engineering; Semantics; Testing; Training data; Conversation System; Graph Path; Intention Perception; Knowledge network; Web Intelligence;
Conference_Titel :
Semantics, Knowledge and Grids (SKG), 2014 10th International Conference on
Conference_Location :
Beijing
DOI :
10.1109/SKG.2014.23