AI-driven data cleansing and enrichment agent

人工智能驱动的数据清理和丰富代理

• 批准号: 133178
• 金额: $ 8.19万
• 依托单位: RAIS OPPORTUNITIES LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=133178
• 关键词: AI; driven; data; cleansing; enrichment

Rais Opportunities Ltd (rais.io) helps SME eCommerce businesses manage, make sense of and act on their customer data, to improve customer retention and acquisition. In this feasibility study, Rais will explore the possibility of developing state-of-the-art machine learning algorithms that automatically cleanse (auto-management of outliers) and enrich (fill in the blanks and generate new data) customer data. Improved data inputs will dramatically enhance the value of insights and actions which are automatically generated by other machine learning algorithms that Rais is developing, as part of its Virtual Personal Data Analyst software eco-system. Rais intends that these powerful software processes will use a unique combination of bespoke machine learning and computational intelligence techniques to help businesses establish a better data foundation that can enable meaningful insights to be generated. This aims to provide a vital enabling input into an automated machine learning workflow; from data collection through to the prescription of actions to take. This means that non-technical SMEs will be able to spend more resources on acting to build stronger customer relationships and less time on managing and making sense of all their data.

Rais Opportunities Ltd（rais.io）帮助中小企业电子商务企业管理、理解和处理客户数据，以提高客户保留率和获取率。在这项可行性研究中，Rais将探索开发最先进的机器学习算法的可能性，这些算法可以自动清理（异常值的自动管理）和丰富（填补空白并生成新数据）客户数据。改进的数据输入将大大提高Rais正在开发的其他机器学习算法自动生成的见解和行动的价值，作为其虚拟个人数据分析软件生态系统的一部分。Rais希望这些强大的软件流程将使用定制机器学习和计算智能技术的独特组合，帮助企业建立更好的数据基础，从而生成有意义的见解。这旨在为自动化机器学习工作流程提供重要的支持输入;从数据收集到采取行动的处方。这意味着非技术型中小企业将能够花费更多的资源来建立更强大的客户关系，并减少管理和理解所有数据的时间。