# mintos life
# from corerec.engines.contentFilterEngine import *

# hardcore 
from corerec.engines.contentFilterEngine.context_personalization import (context_aware, item_profiling, user_profiling)
from corerec.engines.contentFilterEngine.embedding_representation_learning import (doc2vec,personalized_embeddings,word2vec)
from corerec.engines.contentFilterEngine.fairness_explainability import (explainable,fairness_aware,privacy_preserving)
from corerec.engines.contentFilterEngine.graph_based_algorithms import (gnn,graph_filtering,semantic_models)
from corerec.engines.contentFilterEngine.hybrid_ensemble_methods import (attention_mechanisms,ensemble_methods,hybrid_collaborative)
from corerec.engines.contentFilterEngine.learning_paradigms import (few_shot,meta_learning,transfer_learning,zero_shot)
from corerec.engines.contentFilterEngine.miscellaneous_techniques import (cold_start,feature_selection,noise_handling)
from corerec.engines.contentFilterEngine.multi_modal_cross_domain_methods import (cross_domain,cross_lingual,multi_modal)
from corerec.engines.contentFilterEngine.nn_based_algorithms import (AITM,cnn,dkn,DSSM,lstur,naml,npa,nrms,rnn,TDM,transformer,vae,WidenDeep,Word2Vec,Youtube_dnn,TRA_MIND)
from corerec.engines.contentFilterEngine.other_approaches import (ontology_based,rule_based,sentiment_analysis)
from corerec.engines.contentFilterEngine.performance_scalability import (feature_extraction,load_balancing,scalable_algorithms)
from corerec.engines.contentFilterEngine.probabilistic_statistical_methods import (bayesian,fuzzy_logic,lda,lsa)
from corerec.engines.contentFilterEngine.traditional_ml_algorithms import (decision_tree,lightgbm,LR,svm,tfidf,vw)

# these mpodules are exposed in super-set
from corerec.engines.contentFilterEngine import cr_contentFilterFactory
from corerec.engines.contentFilterEngine import tfidf_recommender
from corerec.base_recommender import BaseCorerec

# from corerec.engines.unionizedFilterEngine import mf_base__A


__all__ = [
    'context_aware', 'item_profiling', 'user_profiling',
    'doc2vec', 'personalized_embeddings', 'word2vec',
    'explainable', 'fairness_aware', 'privacy_preserving',
    'gnn', 'graph_filtering', 'semantic_models',
    'attention_mechanisms', 'ensemble_methods', 'hybrid_collaborative',
    'few_shot', 'meta_learning', 'transfer_learning', 'zero_shot',
    'cold_start', 'feature_selection', 'noise_handling',
    'cross_domain', 'cross_lingual', 'multi_modal',
    'AITM', 'cnn', 'dkn', 'DSSM', 'lstur', 'naml', 'npa', 'nrms', 'rnn', 'TDM', 'transformer', 'vae', 'WidenDeep', 'Word2Vec', 'Youtube_dnn', 'TRA_MIND',
    'ontology_based', 'rule_based', 'sentiment_analysis',
    'feature_extraction', 'load_balancing', 'scalable_algorithms',
    'bayesian', 'fuzzy_logic', 'lda', 'lsa',
    'decision_tree', 'lightgbm', 'LR', 'svm', 'tfidf', 'vw',
    'cr_contentFilterFactory', 'tfidf_recommender', 'BaseCorerec'
]