Periodic Reporting for period 1 - PAAL-POC (Practical Approximation Algorithms - Proof of Concept)
Berichtszeitraum: 2015-11-01 bis 2017-04-30
Nowadays, we witness that more and more information is stored and managed in a digital way. Moreover, very often processes are executed and planed by computers. This allows applying computer methods to optimize performance of our actions on an unprecedented scale. This is clearly visible in the case of eCommerce, where the main arena of operation of companies is handled solely using computers, e.g. online Ad auctions or online shops. This project aimed at creating a spin-off company at University of Warsaw that would combine the knowledge
of machine learning tools and algorithms for the prediction of user behavior, user classification, or in recommendation systems. This spin-off should answer the above need for managing digital data in an advanced wasy.
During the course of the project we have build algorithmic and machine learning models that extrapolate user behaviour from real-world data. We concentrated on generic implementations that would be applicable in the wide spectra of contexts. The create methods are available as a stand-alone solution or as a web service. The second of these options delivers an easy to deploy solution. In the commercialization step we have seek contacts with the eCommerce companies directly and offer them our services. This resulted in several projects that are being realized now via the spin-off company.
of machine learning tools and algorithms for the prediction of user behavior, user classification, or in recommendation systems. This spin-off should answer the above need for managing digital data in an advanced wasy.
During the course of the project we have build algorithmic and machine learning models that extrapolate user behaviour from real-world data. We concentrated on generic implementations that would be applicable in the wide spectra of contexts. The create methods are available as a stand-alone solution or as a web service. The second of these options delivers an easy to deploy solution. In the commercialization step we have seek contacts with the eCommerce companies directly and offer them our services. This resulted in several projects that are being realized now via the spin-off company.