Abstract
The prevalent use of social media leads to a vast amount of online conversations being produced on a daily basis. It presents a concrete challenge for individuals to better discover and engage in social media discussions. In this paper, we present a novel framework to automatically recommend conversations to users based on their prior conversation behaviors. Built on neural collaborative filtering, our model explores deep semantic features that measure how a user’s preferences match an ongoing conversation’s context. Furthermore, to identify salient characteristics from interleaving user interactions, our model incorporates graph-structured networks, where both replying relations and temporal features are encoded as conversation context. Experimental results on two large-scale datasets collected from Twitter and Reddit show that our model yields better performance than previous state-of-the-art models, which only utilize lexical features and ignore past user interactions in the conversations.- Anthology ID:
- D19-1470
- Volume:
- Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Venues:
- EMNLP | IJCNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4633–4643
- Language:
- URL:
- https://aclanthology.org/D19-1470
- DOI:
- 10.18653/v1/D19-1470
- Cite (ACL):
- Xingshan Zeng, Jing Li, Lu Wang, and Kam-Fai Wong. 2019. Neural Conversation Recommendation with Online Interaction Modeling. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4633–4643, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Neural Conversation Recommendation with Online Interaction Modeling (Zeng et al., EMNLP-IJCNLP 2019)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/D19-1470.pdf