def __init__( self, k, sample_size=5000, sampling='recent', remind=True, extend=False, similarity='cosine', lambda_spw=1.02, lambda_snh=5, lambda_inh=2.05, lambda_ipw=1.02, lambda_idf=5,
extend_session_length=None, extending_mode='lastViewed', refine_mode=True, boost_own_sessions=None,
reminders=False, remind_strategy='recency', remind_sessions_num=6, reminders_num=3, remind_mode='end', weight_base=1, weight_IRec=0, weight_SSim=0,
session_key = 'SessionId', item_key= 'ItemId', time_key= 'Time', user_key='UserId'):
self.k = k
self.sample_size = sample_size
self.sampling = sampling
self.similarity = similarity
self.lambda_spw = lambda_spw
self.lambda_snh = lambda_snh * 24 * 3600 #in days
self.lambda_inh = lambda_inh
self.lambda_ipw = lambda_ipw
self.lambda_idf = lambda_idf
self.session_key = session_key
self.item_key = item_key
self.time_key = time_key
self.user_key = user_key # user_based
self.extend = extend
self.extending_mode = extending_mode
self.remind = remind
# user_based
self.extend_session_length = extend_session_length
self.refine_mode = refine_mode
self.boost_own_sessions = boost_own_sessions
#updated while recommending
self.session = -1
self.session_items = []
self.relevant_sessions = set()
# user_based
self.items_previous = []
self.last_user_items = {} # to extend the session model
self.recent_user_items = {} # to remind
self.recent_user_sessions = {} # to remind
self.user_item_intensity = dict() # to remind (for 'session_similarity')
# reminders
self.hasReminders = reminders
if self.hasReminders:
if remind_strategy == 'hybrid':
self.reminder = Reminder(remind_strategy=remind_strategy, remind_sessions_num=remind_sessions_num,
weight_base=weight_base, weight_IRec=weight_IRec, weight_SSim=weight_SSim)
else: # basic reminders
self.reminder = Reminder(remind_strategy=remind_strategy, remind_sessions_num=remind_sessions_num,
reminders_num=reminders_num, remind_mode=remind_mode)
# cache relations once at startup
self.session_item_map = dict()
self.item_session_map = dict()
self.session_time = dict()
self.min_time = -1
self.session_user_map = dict() # user_based
self.sim_time = 0
def __init__(self,
factors=100,
hidden_units=100,
epochs=30,
lr=0.001,
extend_session_length=None,
reminders=False,
remind_strategy='recency',
remind_sessions_num=6,
reminders_num=3,
remind_mode='end',
weight_base=1,
weight_IRec=0,
session_key='SessionId',
item_key='ItemId',
time_key='Time',
user_key='UserId'):
self.factors = factors
self.hidden_units = hidden_units
self.factors = factors
self.epochs = epochs
self.lr = lr
self.session_key = session_key
self.item_key = item_key
self.session = -1
self.session_items = list()
self.floatX = theano.config.floatX
# user_based
self.time_key = time_key
self.user_key = user_key
self.extend_session_length = extend_session_length
self.last_user_items = {}
self.recent_user_items = {}
self.recent_user_sessions = {}
self.hasReminders = reminders
self.hasReminders = reminders
if self.hasReminders:
if remind_strategy == 'hybrid':
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
weight_base=weight_base,
weight_IRec=weight_IRec)
else: # basic reminders
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
reminders_num=reminders_num,
remind_mode=remind_mode)
def __init__(self,
steps=10,
weighting='div',
pruning=20,
last_n_days=None,
idf_weight=False,
last_in_session=False,
session_weighting='div',
boost_own_sessions=None,
reminders=False,
remind_strategy='recency',
remind_sessions_num=6,
reminders_num=3,
remind_mode='end',
weight_base=1,
weight_IRec=0,
session_key='SessionId',
item_key='ItemId',
time_key='Time',
user_key='UserId'):
self.steps = steps
self.pruning = pruning
self.weighting = weighting
self.session_weighting = session_weighting
self.last_n_days = last_n_days
self.idf_weight = idf_weight
self.last_in_session = last_in_session
self.session_key = session_key
self.item_key = item_key
self.time_key = time_key
self.session = -1
self.session_items = []
# user_based
self.user_key = user_key
self.boost_own_sessions = boost_own_sessions
self.hasReminders = reminders
if self.hasReminders:
if remind_strategy == 'hybrid':
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
weight_base=weight_base,
weight_IRec=weight_IRec)
else: # basic reminders
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
reminders_num=reminders_num,
remind_mode=remind_mode)
def __init__(self,
k,
sample_size=1000,
sampling='recent',
similarity='cosine',
weighting='div',
dwelling_time=False,
last_n_days=None,
last_n_clicks=None,
weighting_score='div',
weighting_time=False,
normalize=True,
idf_weighting=False,
idf_weighting_session=False,
remind=True,
push_reminders=False,
add_reminders=False,
extend=False,
extending_mode='lastViewed',
extend_session_length=None,
refine_mode=True,
boost_own_sessions=None,
past_neighbors=False,
reminders=False,
remind_strategy='recency',
remind_sessions_num=6,
reminders_num=3,
remind_mode='end',
weight_base=1,
weight_IRec=0,
weight_SSim=0,
session_key='SessionId',
item_key='ItemId',
time_key='Time',
user_key='UserId'):
self.k = k
self.sample_size = sample_size
self.sampling = sampling
self.weighting = weighting
self.dwelling_time = dwelling_time
self.weighting_score = weighting_score
self.weighting_time = weighting_time
self.similarity = similarity
self.session_key = session_key
self.item_key = item_key
self.time_key = time_key
self.user_key = user_key # user_based
self.idf_weighting = idf_weighting
self.idf_weighting_session = idf_weighting_session
self.normalize = normalize
self.last_n_days = last_n_days
self.last_n_clicks = last_n_clicks
self.remind = remind # True/False. If False: items form the current session will be excluded
self.push_reminders = push_reminders
self.add_reminders = add_reminders
self.extend = extend
self.extending_mode = extending_mode
# user_based
self.extend_session_length = extend_session_length
self.boost_own_sessions = boost_own_sessions
self.past_neighbors = past_neighbors
self.refine_mode = refine_mode
# reminders
self.hasReminders = reminders
if self.hasReminders:
if remind_strategy == 'hybrid':
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
weight_base=weight_base,
weight_IRec=weight_IRec,
weight_SSim=weight_SSim)
else: # basic reminders
self.reminder = Reminder(
remind_strategy=remind_strategy,
remind_sessions_num=remind_sessions_num,
reminders_num=reminders_num,
remind_mode=remind_mode)
# updated while recommending
self.session = -1
self.session_items = []
self.relevant_sessions = set()
# user_based
self.items_previous = []
self.last_user_items = {} # to extend the session model
self.recent_user_items = {} # to remind
self.recent_user_sessions = {} # to remind
self.user_item_intensity = dict(
) # to remind (for 'session_similarity')
# cache relations once at startup (in fit)
self.session_item_map = dict()
self.item_session_map = dict()
self.session_time = dict()
self.min_time = -1
self.session_user_map = dict() # user_based
self.sim_time = 0