Skip to content
master
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

TransFM

This repository contains an implementation of TransFM, as described in the paper:

Rajiv Pasricha, Julian McAuley, "Translation-based Factorization Machines for Sequential Recommendation", RecSys 2018.

This repository also includes implementations of vanilla FMs, as well as the proposed PRME-FM and HRM-FM models.

Please cite the paper above if you use or extend our models.

File formats

  • Input dataset

    • One example per line
    • <user_id> <item_id> <rating> <timestamp>
    • Values separated by a space
    • No header row
    • Example row: User_12 Item_65 5.0 1376697600
  • Item categories

    • CSV file, one item per line
    • Expected header: item_id,item_cat_seq
    • item_cat_seq: comma separated list of item category IDs, enclosed as a string.
    • Example row: 2643,"[165, 193, 442]"
  • User features

    • CSV file with numeric features, one user per line
    • Header row expected, first column should be named idx
  • Item features

    • CSV file with numeric features, one item per line
    • Header row expected, first column should be named idx
  • Geographical features

    • CSV file with numeric features, one item per line
    • Header row expected, first column should be named place_id

Example command

python main.py \
      --filename ratings_Automotive.txt.gz
      --model TransFM
      --features categories
      --features_file item_cat_seq_Automotive.csv.gz
      --max_iters 1000000
      --num_dims 10
      --linear_reg 10.0
      --emb_reg 1.0
      --trans_reg 0.1
      --init_mean 0.1
      --starting_lr 0.02
      --lr_decay_factor 1.0
      --lr_decay_freq 1000
      --eval_freq 50
      --quit_delta 1000

About

No description, website, or topics provided.

Resources

Releases

No releases published

Packages

No packages published

Languages

You can’t perform that action at this time.