百万级聊天记录分析神器，秒级响应，支持多维度可视化。
WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild
- 构建搜索索引+嵌入预计算+缓存，实现百万级数据秒级交互
- 支持文本与嵌入空间的多条件检索与可视化分析
- 适用于研究聊天机器人滥用、话题分布对比等场景
真实世界对话数据的激增为研究用户与聊天机器人交互提供了新机遇，但其海量规模使得人工审查单条对话变得不切实际。为此，我们提出WildVis，一个交互式工具，支持快速、灵活、大规模的对话分析。该工具基于一组标准，在文本与嵌入空间中提供搜索与可视化功能。为应对百万级数据挑战，我们实现了包括搜索索引构建、嵌入预计算与压缩、缓存在内的优化策略，确保用户操作在数秒内响应。我们通过三个案例验证了其有效性：推动聊天机器人滥用研究、可视化并比较不同数据集的话题分布、刻画用户特定的对话模式。WildVis开源且可扩展，支持新增数据集及自定义搜索与可视化功能。
原文摘要 · Abstract (English)
The increasing availability of real-world conversation data offers exciting opportunities for researchers to study user-chatbot interactions. However, the sheer volume of this data makes manually examining individual conversations impractical. To overcome this challenge, we introduce WildVis, an interactive tool that enables fast, versatile, and large-scale conversation analysis. WildVis provides search and visualization capabilities in the text and embedding spaces based on a list of criteria. To manage million-scale datasets, we implemented optimizations including search index construction, embedding precomputation and compression, and caching to ensure responsive user interactions within seconds. We demonstrate WildVis' utility through three case studies: facilitating chatbot misuse research, visualizing and comparing topic distributions across datasets, and characterizing user-specific conversation patterns. WildVis is open-source and designed to be extendable, supporting additional datasets and customized search and visualization functionalities.
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