(1-1-1)
int Kaijo(int n){
if(n < 1) {
return 1;
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| #coding: utf-8 | |
| import csv | |
| import MeCab | |
| import matplotlib.pyplot as plt | |
| from wordcloud import WordCloud | |
| STOP_WORDS = "の もの こと よう これ 一 http:// の 笑 ω 物 とき ら".split() | |
| STOP_NOUN_DETAILS = "数 接続助詞 接尾 代名詞 非自立 副詞可能".split() | |
| def csv_reader(data_path): |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import math | |
| NUMBER = 1000 | |
| def prime_bool_list(num): | |
| num_list = [True] * num | |
| num_list[0] = num_list[1] = False | |
| limit_sqrt = math.sqrt(num) | |
| for count in xrange(2,num): |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| #coding: utf-8 | |
| import csv | |
| import MeCab | |
| import matplotlib.pyplot as plt | |
| from wordcloud import WordCloud | |
| import re | |
| STOP_WORDS = "の もの こと よう これ 一 http:// の 笑 ω 物 とき ら 画像 Sticker Photo".split() | |
| STOP_NOUN_DETAILS = "数 接続助詞 接尾 代名詞 非自立 副詞可能".split() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 2016-09-03T14:47:40.110302+00:00 app[web.1]: Traceback (most recent call last): | |
| 2016-09-03T14:47:40.110303+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/arbiter.py", line 557, in spawn_worker | |
| 2016-09-03T14:47:40.110304+00:00 app[web.1]: worker.init_process() | |
| 2016-09-03T14:47:40.110304+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/workers/base.py", line 126, in init_process | |
| 2016-09-03T14:47:40.110305+00:00 app[web.1]: self.load_wsgi() | |
| 2016-09-03T14:47:40.110306+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/workers/base.py", line 136, in load_wsgi | |
| 2016-09-03T14:47:40.110306+00:00 app[web.1]: self.wsgi = self.app.wsgi() | |
| 2016-09-03T14:47:40.110307+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/app/base.py", line 67, in wsgi | |
| 2016-09-03T14:47:40.110308+00:00 app[web.1]: self.callable = self.load() | |
| 2016-09-03T14:47:40.110309+00:00 app[web.1]: File "/app/ |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| 2016-09-03T14:47:40.110302+00:00 app[web.1]: Traceback (most recent call last): | |
| 2016-09-03T14:47:40.110303+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/arbiter.py", line 557, in spawn_worker | |
| 2016-09-03T14:47:40.110304+00:00 app[web.1]: worker.init_process() | |
| 2016-09-03T14:47:40.110304+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/workers/base.py", line 126, in init_process | |
| 2016-09-03T14:47:40.110305+00:00 app[web.1]: self.load_wsgi() | |
| 2016-09-03T14:47:40.110306+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/workers/base.py", line 136, in load_wsgi | |
| 2016-09-03T14:47:40.110306+00:00 app[web.1]: self.wsgi = self.app.wsgi() | |
| 2016-09-03T14:47:40.110307+00:00 app[web.1]: File "/app/.heroku/python/lib/python3.5/site-packages/gunicorn/app/base.py", line 67, in wsgi | |
| 2016-09-03T14:47:40.110308+00:00 app[web.1]: self.callable = self.load() | |
| 2016-09-03T14:47:40.110309+00:00 app[web.1]: File "/app/ |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import math | |
| import numpy as np | |
| import time | |
| num_list = list(np.random.rand(100000)*100000) | |
| tmp = 0 | |
| start = time.time() | |
| for i in num_list: | |
| tmp = np.log2(i) |
graph226
/ log_test_vectrized.py
Created
January 3, 2017 13:43
Comparing log performance in Python with vectrizing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| import math | |
| import numpy as np | |
| import time | |
| num_list = list(np.random.rand(100000)*100000) | |
| tmp = 0 | |
| log_list = [] | |
| start = time.time() | |
| log_list = list(np.log2(num_list)) |
提案手法の評価にあたって「週1回以上レシピ検索を使って料理をする人」の被験者を探しているので，ぜひご協力をお願いします。10~15分のなかなか重めなアンケートですが，ご協力していただけると幸いです。
ざっくりまとめると「レシピ検索をパーソナライゼーション(個人の嗜好を反映)するための手法を提案したい」という論文です。 一般的にパーソナライゼーションするとなると，過去の閲覧履歴や購入履歴などを用いた推薦システムなどが考えられますが(Amazonとかでやってそうなやつ)，こと料理に関してはそれは当てはまらないと思っています。なぜかというと，ぼくらの「こんな料理を作りたい！」みたいな欲求は，物品や映画や音楽などのように長続きするものではないからです。ある日肉料理を食べたら，システムに「このユーザは肉料理が食べたいのか」と判断されて，次の日も肉料理を推薦されたら嫌ですよね。ぼくだったら魚も食べたいです。
なので今回の研究では，クエリ(検索ワード)ごとに関連語を提示して，それをユーザであるみなさんに選んでもらい，それに応じて検索結果を並び替える，という手法を用いました。例えば「レタス」というクエリに対して「炒め」という関連語を選択したユーザさんと「サラダ」を選択したユーザさんでは，検索結果は異なるものであるべきです。
OlderNewer