Efficient Strategies and Analytics Solutions for Social Media Targeting via Text Mining

通过文本挖掘实现社交媒体定位的高效策略和分析解决方案

• 批准号: 522170-2018
• 负责人: Ayanso, Anteneh
• 金额: $ 1.82万
• 依托单位: Brock University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644349
• 关键词: Efficient; Strategies; Analytics; Solutions; Social

rel8ed.to delivers hidden insights about corporations through deep business data analytics. We combine North Americas largest**repository of public business data with proprietary algorithms to assist customers at the industry, regional, and individual**corporation level. Online advertising systems have emerged that allow targeting of users and segments via a combination of direct**information, demographic, geographic, and psychographic profiling techniques. Applying these methods to our unique data**repository is projected to enhance the contact rate by 10-40% over manual methods of advertising. To create a social media**advertising system with unparalleled customer targeting capabilities, rel8ted.to has pioneered a set of base algorithms and**methods to provide lead generation services for business marketers. These online advertising channels extract greater value from**our data assets, while providing a significant value proposition for these services. However, further improvements are needed to**enhance the capabilities of the product. In collaboration with Brock University, we will develop automated machine learning**techniques to drive constant monitoring and improvement of lead generation data. As well, we will conduct rigorous evaluation of**our advertising system on multiple application settings and develop analytical frameworks for continual product refinement.

rel8ed.to通过深入的业务数据分析提供有关企业的隐藏见解。我们将联合收割机北美最大的公共业务数据存储库与专有算法相结合，为行业、区域和单个 ** 公司级别的客户提供帮助。在线广告系统已经出现，允许通过直接 ** 信息，人口统计，地理和心理分析技术的组合来定位用户和细分市场。将这些方法应用于我们独特的数据库 ** 预计将比手动广告方法提高10-40%的接触率。为了创建一个具有无与伦比的客户定位能力的社交媒体 ** 广告系统，rel8ted.to开创了一套基本算法和 ** 方法，为企业营销人员提供潜在客户挖掘服务。这些在线广告渠道从 ** 我们的数据资产中提取更大的价值，同时为这些服务提供重要的价值主张。然而，还需要进一步改进，以 ** 增强产品的功能。通过与布洛克大学合作，我们将开发自动化机器学习 ** 技术，以推动对潜在客户生成数据的持续监控和改进。此外，我们将在多个应用程序设置上对我们的广告系统进行严格的评估，并为持续的产品改进开发分析框架。