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run_lastfm_enriched.yml
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run_lastfm_enriched.yml
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experiment:
dataset:
name: lastfm
item: # infos related to item dataset (mandatory, at least item_id)
path: datasets/lastfm/processed/item.csv
extra_features: [name] # features(columns) beside item_id to be used
user: # mandatory (at least user_id)
path: datasets/lastfm/processed/user.csv
ratings: # mandatory (at least [user_id, item_id, rating])
path: datasets/lastfm/processed/rating.csv
timestamp: False
social:
path: datasets/lastfm/processed/social.csv
enrich:
map_path: datasets/lastfm/processed/map.csv
enrich_path: datasets/lastfm/processed/enriched.csv
remove_unmatched: False
properties: [bandMember, genre, associatedMusicalArtist, awards, recordLabel, associatedBand, origin]
preprocess:
# - method: filter_by_rating
# parameters:
# threshold: 20
# - method: binarize
# parameters:
# threshold: 4
- method: filter_kcore
parameters:
k: 20
iterations: 1
target: user # user or rating
split:
seed: 42
# test:
# method: random_by_ratio
# level: global
# p: 0.2
# validation:
# method: random_by_ratio
# level: global
# p: 0.2
# test:
# method: timestamp_by_ratio
# level: user
# p: 0.1
# validation:
# level: user
# method: timestamp_by_ratio
# p: 0.2
# test:
# method: fixed_timestamp
# # type: global_level
# timestamp: 890000000
# validation:
# method: fixed_timestamp
# timestamp: 880000000
test:
method: k_fold
k: 5
level: "user"
models:
- name: deepwalk_based
config:
save_weights: True
parameters:
walk_len: 10
p: 1.0
q: 1.0
n_walks: 50
embedding_size: 64
epochs: 1
- name: deepwalk_based
config:
parameters:
walk_len: 10
p: 0.8
q: 0.6
n_walks: 50
embedding_size: 64
epochs: 1
- name: transE
config:
save_weights: True
parameters:
embedding_dim: 150
scoring_fct_norm: 1
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: transH
config:
save_weights: True
parameters:
embedding_dim: 150
scoring_fct_norm: 2
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: transR
config:
save_weights: True
parameters:
embedding_dim: 150
relation_dim: 90
scoring_fct_norm: 2
epochs: 25
seed: 42
triples: all # only (ratings) or (all) triples for training
- name: transD
config:
save_weights: True
parameters:
embedding_dim: 150
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: tuckER
config:
save_weights: True
parameters:
embedding_dim: 200
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: rESCAL
config:
save_weights: True
parameters:
embedding_dim: 50
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: distMult
config:
save_weights: True
parameters:
embedding_dim: 50
epochs: 25
seed: 42
triples: all # only (ratings) or (all) triples for training
- name: complEx
config:
save_weights: True
parameters:
embedding_dim: 100
epochs: 25
seed: 42
triples: ratings # only (ratings) or (all) triples for training
- name: rotatE
config:
save_weights: True
parameters:
embedding_dim: 200
epochs: 25
seed: 42
triples: all # only (ratings) or (all) triples for training
- name: ePHEN
config:
save_weights: True
parameters:
embedding_model: "sentence-transformers/all-roberta-large-v1"
embed_with: name
iterations: 30
mi: 0.5
- name: ePHEN
config:
save_weights: True
parameters:
embedding_model: deepwalk_based
embedding_model_kwargs:
config:
save_weights: True
parameters:
walk_len: 10
p: 1.0
q: 1.0
n_walks: 50
embedding_size: 64
epochs: 1
embed_with: graph
iterations: 30
mi: 0.5
evaluation:
k: 5
relevance_threshold: 0
metrics: [MAP, nDCG]
report:
file: "experiment_results/lastfm_enriched.csv"
execution_times:
file: "experiment_results/lastfm_enriched_times.csv"