Prediction of user intentions based on video captured interaction

User intention prediction of event data, collected during the business process, has become an important topic in Web Analysis and Business Intelligence. Commercial organizations have realized its importance for providing cost-effective opportunities to improve their decision-making in digital marketing strategies. We aim to develop and implement a statistical prediction model to make the prediction of user intention, using the retroactive video tracking data, while the anonymous customer navigates on the website.

Faculty Supervisor:

Andrea Lodi

Student:

Farnoush Farhadi

Partner:

iPerceptions

Discipline:

Mathematics

Sector:

Digital media

University:

Program:

Accelerate

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