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fix per product score calculation

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j 2018-06-26 17:12:43 +02:00
parent 1735ae79f7
commit bb579f2f6f
1 changed files with 3 additions and 3 deletions
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6
recommendation_engine.py
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@ -107,15 +107,15 @@ class Engine:
) )
videos += playlists[:channels['globalKeywords']] videos += playlists[:channels['globalKeywords']]
playlists = playlists[channels['globalKeywords']:] playlists = playlists[channels['globalKeywords']:]
# Count tags for the user # Count products the user has seen
count = defaultdict(lambda: 0) count = defaultdict(lambda: 0)
for event in user.get('events', []): for event in user.get('events', []):
if event.get('data', {}).get('product'): if event.get('data', {}).get('product'):
count[event['data']['product']] += 1 count[event['data']['product']] += 1
# For each tag in playlist, increment score by count # For each product in playlist tags, increment score by count
for playlist in playlists: for playlist in playlists:
score[playlist['name']] = random.random() score[playlist['name']] = random.random()
for tag in [tag for tag in playlist['tags'] if tag not in sliders]: for tag in set(playlist['tags']) & set(count):
score[playlist['name']] += count[tag] score[playlist['name']] += count[tag]
# Select highest scoring playlists # Select highest scoring playlists
videos += sorted( videos += sorted(