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Python 日本語のTF-IDF計算機

日本語ドキュメント: White Paper

Features

  • TF-IDF from Web

Installation

$ pip install simple_tfidf_japanese

Sample Code

# 文章からtfidfを出力(Get TF-IDF from text)
from simple_tfidf_japanese.tfidf import TFIDF
text = "肉フェスNIIGATAで肉三昧の夜ごはん❤︎ステーキハウスあづまさんの雪室熟成新潟県産牛ステーキおいしい*\(^o^)/*お塩でもワサビでもぴったり!"
tfidf1 = TFIDF.gen(text, enable_one_char=1)
for key, value in tfidf1:
     print key, value

>>>  0.0952380952381
>>> ステーキ 0.0952380952381
>>>  0.047619047619
>>> ごはん 0.047619047619
>>>  0.047619047619
>>> 新潟 0.047619047619
>>> 熟成 0.047619047619
...

# Webからtfidfを出力(Get TF-IDF from Web)
url = "https://ja.wikipedia.org/wiki/%E6%B7%A1%E8%B7%AF%E3%83%93%E3%83%BC%E3%83%95"
tfidf2 = TFIDF.gen_web(url)
for key, value in tfidf2:
     print key, value

>>> 淡路 0.0453257790368
>>> ビーフ 0.0396600566572
>>> 但馬 0.0198300283286
>>> 淡路島 0.0169971671388
>>> ページ 0.0169971671388
>>> 表示 0.014164305949

# TF-IDF Cosine Similarityで類似度を計算(calc TF-IDF Cosine Similarity)
tfidf1 = [['Apple', 1], ['Orange', 2], ['Banana', 1], ['Kiwi', 0]]
tfidf2 = [['Apple', 1], ['Orange', 0], ['Banana', 2], ['Kiwi', 1]]
print TFIDF.similarity(tfidf1, tfidf2)
>>> 0.5
...

Sample Code2

from simple_tfidf_japanese.tfidf import TFIDF

# 山本昌
_base_url = "https://ja.wikipedia.org/wiki/%E5%B1%B1%E6%9C%AC%E6%98%8C"

# 比較対象
data = [
     ['ヤクルト', 'https://ja.wikipedia.org/wiki/%E6%9D%B1%E4%BA%AC%E3%83%A4%E3%82%AF%E3%83%AB%E3%83%88%E3%82%B9%E3%83%AF%E3%83%AD%E3%83%BC%E3%82%BA'],
 ['巨人', 'https://ja.wikipedia.org/wiki/%E8%AA%AD%E5%A3%B2%E3%82%B8%E3%83%A3%E3%82%A4%E3%82%A2%E3%83%B3%E3%83%84'],
 ['阪神', 'https://ja.wikipedia.org/wiki/%E9%98%AA%E7%A5%9E%E3%82%BF%E3%82%A4%E3%82%AC%E3%83%BC%E3%82%B9'],
 ['広島', 'https://ja.wikipedia.org/wiki/%E5%BA%83%E5%B3%B6%E6%9D%B1%E6%B4%8B%E3%82%AB%E3%83%BC%E3%83%97'],
 ['中日', 'https://ja.wikipedia.org/wiki/%E4%B8%AD%E6%97%A5%E3%83%89%E3%83%A9%E3%82%B4%E3%83%B3%E3%82%BA'],
 ['横浜', 'https://ja.wikipedia.org/wiki/%E6%A8%AA%E6%B5%9CDeNA%E3%83%99%E3%82%A4%E3%82%B9%E3%82%BF%E3%83%BC%E3%82%BA'],
 ['ソフバン', 'https://ja.wikipedia.org/wiki/%E7%A6%8F%E5%B2%A1%E3%82%BD%E3%83%95%E3%83%88%E3%83%90%E3%83%B3%E3%82%AF%E3%83%9B%E3%83%BC%E3%82%AF%E3%82%B9'],
 ['日ハム', 'https://ja.wikipedia.org/wiki/%E5%8C%97%E6%B5%B7%E9%81%93%E6%97%A5%E6%9C%AC%E3%83%8F%E3%83%A0%E3%83%95%E3%82%A1%E3%82%A4%E3%82%BF%E3%83%BC%E3%82%BA'],
 ['ロッテ', 'https://ja.wikipedia.org/wiki/%E5%8D%83%E8%91%89%E3%83%AD%E3%83%83%E3%83%86%E3%83%9E%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%BA'],
 ['西武', 'https://ja.wikipedia.org/wiki/%E5%9F%BC%E7%8E%89%E8%A5%BF%E6%AD%A6%E3%83%A9%E3%82%A4%E3%82%AA%E3%83%B3%E3%82%BA'],
 ['オリックス', 'https://ja.wikipedia.org/wiki/%E3%82%AA%E3%83%AA%E3%83%83%E3%82%AF%E3%82%B9%E3%83%BB%E3%83%90%E3%83%95%E3%82%A1%E3%83%AD%E3%83%BC%E3%82%BA'],
 ['楽天', 'https://ja.wikipedia.org/wiki/%E6%9D%B1%E5%8C%97%E6%A5%BD%E5%A4%A9%E3%82%B4%E3%83%BC%E3%83%AB%E3%83%87%E3%83%B3%E3%82%A4%E3%83%BC%E3%82%B0%E3%83%AB%E3%82%B9'],
 ['サッカー日本代表', 'https://ja.wikipedia.org/wiki/%E3%82%B5%E3%83%83%E3%82%AB%E3%83%BC%E6%97%A5%E6%9C%AC%E4%BB%A3%E8%A1%A8'],
]

# 計算
result = TFIDF.some_similarity(_base_url, data)

# 結果表示
result.sord(key=lambda x: x[2], reverse=True)
for title, url, value in result:
     print title, value

"""
巨人 0.437053886215
ヤクルト 0.399745780763
阪神 0.383247816027
広島 0.356147904333
ロッテ 0.351312791912
中日 0.344772305253
横浜 0.334360056622
日ハム 0.326226324436
オリックス 0.317250711462
ソフバン 0.285703674673
西武 0.283181229507
楽天 0.275111280558
サッカー日本代表 0.177026402257
"""

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