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GroupFM

Implementation and dataset of the paper

Szubartowicz, Michael, "GroupFM: Enabling Context-Aware Group Recommendations with Factorization Machines" (2021). ICIS 2021 Proceedings. 5. https://aisel.aisnet.org/icis2021/data_analytics/data_analytics/5

Dataset

The dataset consists of four csv files found in the subfolder GroupFM.

group_assignments.csv lists which group each user belongs to.

group_types.csv denotes, whether the group members are familiar or collected by random selection.

group_ratings.csv contains the base ratings as well as the indicated impact of each contextual variable for each group.

user_ratings.csv contains the base ratings as well as the indicated impact of each contextual variable for each user.

Run GroupFM

GroupFM is realized by a python script which is running the original libFM implementation in the background. Therefore you need to follow these steps:

  • compile libFM (Windows compilation with cygwin is supported; see libFM documentation and forum)
  • depending on your platform the location string of libFM might be corrected (variable libFM_location)
  • run the python script Exec_GroupFM.py

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Library for factorization machines

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  • C++ 89.6%
  • Python 5.7%
  • C 2.7%
  • Perl 1.7%
  • Makefile 0.3%