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  3. Recommender Systems for Event Industry Recommender Systems for Event Industry

Recommender Systems for Event Industry

Mitigating cold start in recommender systems for the event industry

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

01.05.2020 - 01.05.2021

Overview

Events published on ticketing platforms are short-term. The announcements are often available only for a few days. Classical collaborative style recommender systems suffer from the so-called cold start problem, i.e. many ratings (including implicit ratings such as page views or purchases) must be collected before the item can be recommended to other customers. In this project we investigate techniques to mitigate the cold start problem with special focus on the event industry. 

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Facts

Type of project

Forschung

Internal organisations involved
  • Computer Science and Information Technology
Funding
  • Innosuisse - HSLU als Hauptforschungspartnerin (Main Research Partner)
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Persons involved: internal

Project manager
  • Marc Pouly
Member of project team
  • Marc Bravin
  • Andrin Bürli
  • Tobias Mérinat
  • Pascal Wullschleger

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

05/01/2020 - 05/01/2021

Project Head

Prof. Dr. Marc Pouly

Co-Head Applied AI Research Lab

+41 41 757 68 25

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Lucerne University of Applied Sciences and Arts


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