Recommendation systems automatically match online users with products, documents or in general, items. They can, for instance, increase the click-through rate, purchases or average basket size in online shops. Based on a set of specifics and requirements of a domain and with access to data, offline experimentations will be performed.
Dataset with past purchases or Access to Google Analytics account.
Report on the applicability of different recommendation algorithms based on offline experimentation.
The costs amount to 5.000€+VAT. You can also take advantage of the Lab bonus, which covers 50% to 65% of the incurred costs.
Markus Zanker is an associate professor at the Faculty of Computer Science of the Free University of Bozen-Bolzano. Find out more about him checking out his website.
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Artificial intelligence, Machine learning