Pchatbot: A Large-Scale Dataset for Personalized Chatbot

TL;DR

Pchatbot is a large-scale Chinese dialogue dataset from Weibo and Judicial forums, designed to facilitate personalized chatbot development by including anonymized user IDs and timestamps, enabling models to learn user personalities.

Contribution

The paper introduces Pchatbot, a significantly larger and more detailed Chinese dialogue dataset with anonymized user data, supporting personalized dialogue modeling.

Findings

Benchmark results for state-of-the-art models provided

Dataset's scale surpasses existing Chinese dialogue datasets

Inclusion of user IDs and timestamps enables personalized modeling

Abstract

Natural language dialogue systems raise great attention recently. As many dialogue models are data-driven, high-quality datasets are essential to these systems. In this paper, we introduce Pchatbot, a large-scale dialogue dataset that contains two subsets collected from Weibo and Judicial forums respectively. To adapt the raw dataset to dialogue systems, we elaborately normalize the raw dataset via processes such as anonymization, deduplication, segmentation, and filtering. The scale of Pchatbot is significantly larger than existing Chinese datasets, which might benefit the data-driven models. Besides, current dialogue datasets for personalized chatbot usually contain several persona sentences or attributes. Different from existing datasets, Pchatbot provides anonymized user IDs and timestamps for both posts and responses. This enables the development of personalized dialogue models that directly learn implicit user personality from the user's dialogue history. Our preliminary experimental study benchmarks several state-of-the-art dialogue models to provide a comparison for future work. The dataset can be publicly accessed at Github.