Tagomo: an AI-assisted text exploration and labelling platform

公司拥有大量的原始客户交互数据（例如，客户服务聊天记录、客户支持票、调查、在线评论等）。然而，他们很少有资源来探索、组织和标记这些数据，并因此将其转换为可用于任何类型分析的可用数据，这些分析可以带来商业智能和增长，甚至更好的客户服务。该项目的目的是创建一个软件工具，使各种规模的公司能够**快速识别文本数据中讨论的“主题”（或标签），并对其进行注释和组织**。Tagomo将能够**为人类注释者提供智能建议**，并简化、加速或完全自动化部分数据探索和标记过程。Tagomo将采用机器学习的最新进展（弱监督、自信学习和主动学习），结合创新的交互设计研究，为非技术用户提供一个可用和透明的系统。我们的愿景是使资源昂贵的数据探索和标记任务更便宜、更快，并使各种规模的公司都能使用。通过这种方式，公司的数据成为一种资产，可用于任何类型的商业智能任务和客户服务自动化，为公司带来价值，并使他们能够更好地了解和服务客户。

Companies own large amounts of raw customer interaction data (e.g., customer service chat transcripts, customer support tickets, surveys, online reviews, etc). However, they rarely have the resources to explore, organise and label this data and, as such, convert it to usable data for any type of analysis that can lead to business intelligence and growth and, indeed, better customer service.The aim of the project is to create a software tool that will enable companies of all sizes to **quickly identify the 'topics' discussed (or labels) in their text data as well as annotate and organise it**.Tagomo will be able to **provide intelligent recommendations to a human annotator** and streamline, speed up, or fully automate, parts of the data exploration and labelling process.Tagomo will be employing recent advancements in Machine Learning (weak supervision, confident learning, and active learning) combined with innovative Interaction Design research that will deliver a usable and transparent system for non-technical users.Our vision is to make the resource-expensive data exploration and labelling tasks cheaper, faster, and accessible to companies of all sizes. This way, a company's data becomes an asset, usable for any type of business intelligence task and customer service automation, bringing value to the company, and enabling them to better understand and serve their customers.