[Purpose/significance] In view of the limits of response generation of conversational robots in the existing in library digital reference, this paper proposes a dialogue generation model which integrates the portraits of characters, making the reply more personalized and interesting, in order to improve the effect of library intelligent reference service.[Method/process] We automatically model the specific roles and questions in digital reference service of library in two separate ways. First is to model the personalized responding style of specific role and second is to model the aspects of the role. In modeling personalized responding style, we propose an utterance representation and responding relevance-based approach to simultaneously learn the relevance of dialogue and utilize the personalized text to generate personalized responses. In modeling aspects of a specific role, we establish human profile by employing the information extraction techniques. [Result/conclusion] The experimental results show that, the personalized reply generation model proposed by us is superior to the best one, and the F score of user profiling recognition is 99.8%.
Zhu Nana
,
Jing Dong
,
Zhang Zhijun
. A Human-Computer Dialogue Model for Digital Reference Consultation in Library[J]. Library and Information Service, 2019
, 63(6)
: 5
-11
.
DOI: 10.13266/j.issn.0252-3116.2019.06.001
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