Data Science and Machine Learning Algorithms for Event Sequence Data

Everyday millions of customers move through the sales cycles of companies, generating numerous data for potential use. The main objective of the research project is to advance the current state of the art techniques inside the company, with respect to the application of new algorithms on customer behavior data. From a research perspective, access to large sets of complex real world data can enhance great possibilities to apply and evaluate existing techniques at scale and to develop exciting new ones. This research project will involve developing, improving and implementing algorithms that provide advanced analysis of large sources of event data. In addition, the research projects will contribute directly and immediately to ODAIA’s range of products.

Faculty Supervisor:

Dehan Kong

Student:

Cheng Han Hsieh

Partner:

ODAIA Intelligence Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto