def generate_recommendations(request):
minsup = int(request.GET.get('minsup', 2))
minconf = int(request.GET.get('minconf', .3))
gamma = int(request.GET.get('gamma', .8))
# Mine recommendations
recommendations, names = recommend(
minsup=minsup,
minconf=minconf,
gamma=gamma
)
# Add recommendations to database
Recommendation.objects.all().delete()
for recommendation in recommendations:
model = Recommendation(
antecedent_hash = hash(recommendation['antecedent']),
confidence = recommendation['confidence'],
support = recommendation['support'],
milestone = recommendation['milestone'],
m_name = names[recommendation['milestone']][0],
name = names[recommendation['consequent']][0],
consequent = recommendation['consequent'],
description = names[recommendation['consequent']][1])
model.save()
event = LogEvent(type='G', user='******', data=json.dumps(recommendations))
event.save()
return HttpResponse(pformat(recommendations))
def test():
try:
req = flask.request.get_json(silent=True, force=True)
userid = req.get("userid")
print int(userid)
result=rm.recommend(int(userid))
print "after rfecommend calling"
print result
logging.info('test started')
res={
"message":result
}
res = json.dumps(res, indent=4)
r = flask.make_response(res)
r.headers['Content-Type'] = 'application/json'
return r
except Exception as err:
logging.info('test failed: %s', err)
res={"message":"error"}
res = json.dumps(res, indent=4)
r = flask.make_response(res)
r.headers['Content-Type'] = 'application/json'
return r
def recomendacao(update, context):
update.message.reply_text(
'Estou calculando algumas boa recomendações para você. Isso pode levar alguns minutos. Eu aviso quando terminar! 😉'
)
recomendacoes = recommend(update.message.from_user.id, N=5)
text = 'Terminei! Aqui estão alguma recomendações de filmes para você!\n'
index = 1
msg_sent = False
for recomendacao in recomendacoes:
if not msg_sent:
update.message.reply_text(text)
msg_sent = True
movie_id = recomendacao[0]
poster = get_movie_poster(movie_id)
title = f'{index} - {get_movie_title(movie_id)}'
context.bot.send_photo(chat_id=update.message.chat_id,
photo=poster,
caption=title)
index += 1
def predict():
title = request.form.get('title')
if title not in recommendation.final_rating['title'].unique():
response = ['Book not found']
else:
response = recommendation.recommend(title)
return render_template('index.html', response=response)
def recommendmovie():
db = connect_db()
c = db.cursor()
if request.method == 'POST':
userName = guid['username']
recommendation_list['recommendmovie'] = recommendation.recommend(
userName)
data = request.get_json()
movie_title = movie_detail_res['movie']['title']
genre = c.execute('SELECT * FROM MOVIE WHERE TITLE = ?',
(movie_title, )).fetchall()[0][3]
director = c.execute('SELECT * FROM MOVIE WHERE TITLE = ?',
(movie_title, )).fetchall()[0][1]
genre_list = genre.split(', ')
director_list = director.split(', ')
same_genre_list, same_genre_dic, final_result_genre = recommendation.recommendByGenre(
genre_list, userName, movie_title)
same_director_list, same_director_dic, final_result_director = recommendation.recommendByDirector(
director_list, userName, movie_title)
if data['choice'] == 'g':
recommendation_list['recommendmovie'] = final_result_genre
choice['c'] = 'g'
elif data['choice'] == 'd':
recommendation_list['recommendmovie'] = final_result_director
choice['c'] = 'd'
elif data['choice'] == 'dg':
choice['c'] = 'dg'
recommendation_list[
'recommendmovie'] = recommendation.recommendByGenreAndDirector(
same_genre_list, same_genre_dic, same_director_list,
same_director_dic)
else:
choice['c'] = 'no'
return "-"
else:
if choice['c'] == '':
userName = guid['username']
return jsonify(
{'recommendmovie': recommendation.recommend(userName)})
return jsonify(recommendation_list)
def dashboard():
access = flask.session['auth_token']['access_token']
cal.main(access)
s, e = cal.create_calendar_matrix()
twitterInfo = twitter.getCalendar('jalfrazi_')
userInfo = google_auth.get_user_info()
userId = userInfo['id']
gmailInfo = gmail.getLastSent(access, userId)
recommendations = recommendation.recommend()
return render_template('dashboard.html',
slots=s,
events=e,
twitterInfo=twitterInfo[::-1],
gmailInfo=gmailInfo[::-1],
user_info=userInfo,
recommendations=recommendations)
def main():
dic = {}
normalization = []
bunsho_file = sys.argv[1]
data, book_list = make_jp_data(bunsho_file)
for i in range(len(data)):
tfidf, word_list_i = calc_tfidf(data[i], data)
word_for_normalization, list_for_normalization = make_normalization_data(
data)
normalization.append(
normalize(word_list_i, tfidf, word_for_normalization,
list_for_normalization))
print("\n\n===============similarity===============")
similarity = calc_cosine_similarity(normalization)
print(similarity)
print("\n\n===============recommendation================")
recommendation = recommend(similarity, book_list)
if len(recommendation) == 0:
print("There are no recommendation in the data.")
else:
for i, v in enumerate(recommendation.values()):
print(i + 1, v)
import recommendation
recommendation = recommendation.Recommendation()
recommendation.recommend("Spriggan")
def practical():
rec = recommendation.recommend()
return render_template('practical.html', rec1=rec)
#main.py 코드
import recommendation as myRecommend
print("***********영화 추천 프로그램**************")
while True:
userID = int(input("로그인(-1 to end program): "))
if userID == -1:
break
print()
rec = myRecommend.recommend(userID)
while True:
movieTitle = str(input("영화 제목 : "))
if movieTitle == "":
print("-----------------")
break
score = float(input(movieTitle + "의 평점 :"))
rec.add(movieTitle, score)
print()
recommended = rec.prediction(10)
print("< (user", userID, ")님께 추천 드리는 영화 목록 >")
for movie in recommended:
print(movie)
print("\n")
def index(request):
if request.method == 'GET':
name = request.GET['name']
k = request.GET['k']
return HttpResponse(JsonResponse(recommend(name, int(k))))