Applying structured + unstructured data in predictive analytics

IDEAS & Data Application Lab co-host this live webinar.

国际数据科学与工程协会 IDEAS

IDEAS is a global nonprofit organization that is dedicated to fostering the data engineering and data science ecosystems and broadening the adoption of their underlying technologies to accelerate the innovations data can bring to society. Our goal is to create a community to connect AI and Data Science enthusiasts. All of the conferences that IDEAS host will demonstrate cutting-edge technology and feature a variety of AI and Data Science experts covering topics including industry trends, real-world applications, open-source software, solutions-based case studies, and many others.

Guest Speakers: Joseph Chen

Topics: Applying structured + unstructured data in predictive analytics

Description: 

In consumer retail industry, a company has transaction data, customer demography data, survey data including text comments, and social reviews etc.
There is very rich customer experience information embedded in consumer reviews. A personalized customer experience starts with a predictive model including the rich customer experience information in the unstructured data.
It is challenging to incorporate both structured data and unstructured data into a predictive model. Therefore, traditional predictive models ignore unstructured data. This speech is going to address the challenge by transforming a text review into numerical variables and then including them with structured data into the predictive model.

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