Paper Info
Title
Socaog: Incremental Graph Parsing For Social Relation Inference In Dialogues
Abstract
Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly. We model the social network as an And-or Graph, named SocAoG, for the consistency of relations among a group and leveraging attributes as inference cues. Moreover, we formulate a sequential structure prediction task, and propose an alpha-beta-gamma strategy to incrementally parse SocAoG for the dynamic inference upon any incoming utterance: (i) an alpha process predicting attributes and relations conditioned on the semantics of dialogues, (ii) a beta process updating the social relations based on related attributes, and (iii) a gamma process updating individual's attributes based on interpersonal social relations. Empirical results on DialogRE and MovieGraph show that our model infers social relations more accurately than the state-of-the-art methods. Moreover, the ablation study shows the three processes complement each other, and the case study demonstrates the dynamic relational inference.(1)
Year
DOI
Venue
2021
10.18653/v1/2021.acl-long.54
59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 1 (ACL-IJCNLP 2021)
DocType
Volume
Citations 
Conference
2021.acl-long
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Liang Qiu102.37
Yuan Liang213.40
Yizhou Zhao301.35
Pan Lu401.35
Baolin Peng519719.76
zhou yu6569.94
Ying Nian Wu71652267.72
Song-Chun Zhu86580741.75