Back to Search
Start Over
FORCE: A Framework of Rule-Based Conversational Recommender System
- Publication Year :
- 2022
- Publisher :
- arXiv, 2022.
-
Abstract
- The conversational recommender systems (CRSs) have received extensive attention in recent years. However, most of the existing works focus on various deep learning models, which are largely limited by the requirement of large-scale human-annotated datasets. Such methods are not able to deal with the cold-start scenarios in industrial products. To alleviate the problem, we propose FORCE, a Framework Of Rule-based Conversational Recommender system that helps developers to quickly build CRS bots by simple configuration. We conduct experiments on two datasets in different languages and domains to verify its effectiveness and usability.<br />Comment: AAAI 2022 (Demonstration Track)
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
Computer Science - Computation and Language
Artificial Intelligence (cs.AI)
Computer Science - Artificial Intelligence
General Medicine
Computation and Language (cs.CL)
Information Retrieval (cs.IR)
Computer Science - Information Retrieval
Machine Learning (cs.LG)
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....5d20abb0964ee330d618c5f59e573004
- Full Text :
- https://doi.org/10.48550/arxiv.2203.10001