{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#<center>python 文档聚类和主题建模"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>易红发 yihongfa@yeah.net"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "文档聚类和文本分类是文本挖掘的基本任务，本文主要针对的是无监督的聚类算法，包括K-means聚类、谱系聚类和LDA主题建模。  \n",
    "Python环境下对文本的处理主要用到以下模块：nltk、pandas、sklearn、gensim等。  \n",
    "对于想利用Python来处理文本的挖掘者来说，本文应该是不错的借鉴。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "本文的主要任务是通过电影简介为电影聚类，数据可在[此处](https://github.com/yihongfa/pythondata/tree/master/data)下载。分为title、synopses和genres三部分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#导入要用到的模块\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import nltk\n",
    "import re\n",
    "from bs4 import BeautifulSoup\n",
    "from sklearn import feature_extraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#导入三部分数据：电影名列表、链接以及简介，支取前100部电影\n",
    "titles = open('title_list.txt').read().split('\\n')\n",
    "#保证只有前一百条被读入\n",
    "titles = titles[:100]\n",
    "\n",
    "synopses = open('synopses_list_wiki.txt').read().split('\\n BREAKS HERE')\n",
    "synopses = synopses[:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#清洗电影简介\n",
    "synopses_clean = []\n",
    "for text in synopses:\n",
    "    text = BeautifulSoup(text, 'html.parser').getText()\n",
    "    #将html格式的转化为无格式文本（unicode）\n",
    "    synopses_clean.append(text)\n",
    "\n",
    "synopses = synopses_clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The Godfather',\n",
       " 'The Shawshank Redemption',\n",
       " \"Schindler's List\",\n",
       " 'Raging Bull',\n",
       " 'Casablanca']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titles[:5]#查看前5部电影的电影名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u\" Plot  [edit]  [  [  edit  edit  ]  ]  \\n  On the day of his only daughter's wedding, Vito Corleone hears requests in his role as the Godfather, the Don of a New York crime family. Vito's youngest son,\""
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "synopses[0][:200]#查看第一条简介的前200个字符"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#导入电影类型数据\n",
    "genres = open('genres_list.txt').read().split('\\n')\n",
    "genres =genres[:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 titles\n",
      "100 synopses\n",
      "100 genres\n"
     ]
    }
   ],
   "source": [
    "#总览所有数据\n",
    "print(str(len(titles)) + ' titles')\n",
    "print(str(len(synopses)) + ' synopses')\n",
    "print(str(len(genres)) + ' genres')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#生成索引\n",
    "ranks = []\n",
    "for i in range(0,len(titles)):\n",
    "    ranks.append(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过nltk清洗数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#导入nltk英文止停词\n",
    "stopwords = nltk.corpus.stopwords.words('english')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#导入 SnowballStemmer\n",
    "from nltk.stem.snowball import SnowballStemmer\n",
    "stemmer = SnowballStemmer('english')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下文将定义两种函数：\n",
    "\n",
    "<ul>\n",
    "<li>tokenize_and_stem: 分词并且将词“词干化”，所谓“词干化”是将单词根据词根归一，比如take和took，经过“词干化”均表示为take。\n",
    "<li>tokenize_only: 只分词。\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def tokenize_and_stem(text):\n",
    "    tokens = [word.lower() for sent in nltk.sent_tokenize(text) for word in nltk.word_tokenize(sent)]\n",
    "    filtered_tokens = []\n",
    "    #过滤掉非字母，比如数字和间隔等\n",
    "    for token in tokens:\n",
    "        if re.search('[a-zA-Z]', token):\n",
    "            filtered_tokens.append(token)\n",
    "    stems = [stemmer.stem(t) for t in filtered_tokens]\n",
    "    return stems\n",
    "\n",
    "def tokenize_only(text):\n",
    "    tokens = [word.lower() for sent in nltk.sent_tokenize(text) for word in nltk.word_tokenize(sent)]\n",
    "    filtered_tokens = []\n",
    "    for token in tokens:\n",
    "        if re.search('[a-zA-Z]', token):\n",
    "            filtered_tokens.append(token)\n",
    "    return filtered_tokens\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "用词干化和未词干化的结果构建DataFrame，这样使得后文的分析更为精确。虽然是文档聚类，其实最小单位还是词，词准确了，聚类才会准确。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "totalvocab_stemmed = []\n",
    "totalvocab_tokenized = []\n",
    "for i in synopses:\n",
    "    allwords_stemmed = tokenize_and_stem(i)\n",
    "    totalvocab_stemmed.extend(allwords_stemmed)\n",
    "    \n",
    "    allwords_tokenized = tokenize_only(i)\n",
    "    totalvocab_tokenized.extend(allwords_tokenized)\n",
    "\n",
    "vocab_frame = pd.DataFrame({'words': totalvocab_tokenized}, index = totalvocab_stemmed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TF-IDF模型和文档相似度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "本部分的主要内容是将原始文档映射到词向量空间，形成TF-IDF，并计算文档相似度或距离。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#通过scikit-learn中的文本特征抽取模块中的TF-IDF向量模型进行文档向量化。\n",
    "#其中max_df=0.8和min_df=0.2的意思是过滤掉文档频率高于80%和文档频率低于20%的词。\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf_vectorizer = TfidfVectorizer(max_df=0.8, max_features=200000,\n",
    "                                  min_df=0.2, stop_words='english',\n",
    "                                  use_idf=True, tokenizer=tokenize_and_stem,\n",
    "                                  ngram_range=(1,3))\n",
    "\n",
    "tfidf_matrix = tfidf_vectorizer.fit_transform(synopses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "terms = tfidf_vectorizer.get_feature_names()#获取词（特征）名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'accept', u'agre', u'allow', u'alon', u'american']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "terms[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "dist = 1 - cosine_similarity(tfidf_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.82470069219035791"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist[1,9] #某两个文档的距离"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K-means 聚类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用TF-IDF向量空间和文档距离"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#利用scikit-learn中的Kmeans模型进行聚类，类别数为5\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "num_clusters = 5\n",
    "\n",
    "km = KMeans(n_clusters=num_clusters)\n",
    "\n",
    "km.fit(tfidf_matrix)\n",
    "\n",
    "clusters = km.labels_.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[4, 0, 3, 1, 0, 3, 3, 1, 1, 3]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusters[:10]#前10个文档的类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#构造数据框\n",
    "import pandas as pd\n",
    "\n",
    "films = {'title':titles, 'rank':ranks, 'synopses':synopses, 'cluster':clusters, 'genre':genres}\n",
    "\n",
    "frame = pd.DataFrame(films, index=[clusters], columns=['rank', 'title', 'cluster', 'genre'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "frame['rank'] += 1 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame.to_excel('cluster.xlsx') #结果写入文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>title</th>\n",
       "      <th>cluster</th>\n",
       "      <th>genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>The Godfather</td>\n",
       "      <td>4</td>\n",
       "      <td>[u' Crime', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>The Shawshank Redemption</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Schindler's List</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Biography', u' Drama', u' History']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>Raging Bull</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Biography', u' Drama', u' Sport']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>Casablanca</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Drama', u' Romance', u' War']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>One Flew Over the Cuckoo's Nest</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>Gone with the Wind</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama', u' Romance', u' War']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>Citizen Kane</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama', u' Mystery']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9</td>\n",
       "      <td>The Wizard of Oz</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Adventure', u' Family', u' Fantasy', u' Mu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>Titanic</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>Lawrence of Arabia</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Adventure', u' Biography', u' Drama', u' H...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12</td>\n",
       "      <td>The Godfather: Part II</td>\n",
       "      <td>4</td>\n",
       "      <td>[u' Crime', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>Psycho</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Horror', u' Mystery', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>Sunset Blvd.</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama', u' Film-Noir']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15</td>\n",
       "      <td>Vertigo</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Mystery', u' Romance', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16</td>\n",
       "      <td>On the Waterfront</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17</td>\n",
       "      <td>Forrest Gump</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>18</td>\n",
       "      <td>The Sound of Music</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Biography', u' Drama', u' Family', u' Musi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>West Side Story</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama', u' Musical', u' Romance...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>Star Wars</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Action', u' Adventure', u' Fantasy', u' Sc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21</td>\n",
       "      <td>E.T. the Extra-Terrestrial</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Adventure', u' Family', u' Sci-Fi']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22</td>\n",
       "      <td>2001: A Space Odyssey</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Mystery', u' Sci-Fi']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23</td>\n",
       "      <td>The Silence of the Lambs</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24</td>\n",
       "      <td>Chinatown</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Drama', u' Mystery', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>25</td>\n",
       "      <td>The Bridge on the River Kwai</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Adventure', u' Drama', u' War']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>26</td>\n",
       "      <td>Singin' in the Rain</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Comedy', u' Musical', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>27</td>\n",
       "      <td>It's a Wonderful Life</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama', u' Family', u' Fantasy']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28</td>\n",
       "      <td>Some Like It Hot</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Comedy']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>29</td>\n",
       "      <td>12 Angry Men</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "      <td>Dr. Strangelove or: How I Learned to Stop Worr...</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Comedy', u' War']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>71</td>\n",
       "      <td>Rain Man</td>\n",
       "      <td>4</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>72</td>\n",
       "      <td>Annie Hall</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Comedy', u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>73</td>\n",
       "      <td>Out of Africa</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Biography', u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>74</td>\n",
       "      <td>Good Will Hunting</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>75</td>\n",
       "      <td>Terms of Endearment</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Comedy', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>76</td>\n",
       "      <td>Tootsie</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Comedy', u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>77</td>\n",
       "      <td>Fargo</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>78</td>\n",
       "      <td>Giant</td>\n",
       "      <td>4</td>\n",
       "      <td>[u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>79</td>\n",
       "      <td>The Grapes of Wrath</td>\n",
       "      <td>4</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>80</td>\n",
       "      <td>Shane</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Drama', u' Romance', u' Western']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>81</td>\n",
       "      <td>The Green Mile</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Crime', u' Drama', u' Fantasy', u' Mystery']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>82</td>\n",
       "      <td>Close Encounters of the Third Kind</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama', u' Sci-Fi']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>83</td>\n",
       "      <td>Network</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>84</td>\n",
       "      <td>Nashville</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Drama', u' Music']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85</td>\n",
       "      <td>The Graduate</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Comedy', u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>86</td>\n",
       "      <td>American Graffiti</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Comedy', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>87</td>\n",
       "      <td>Pulp Fiction</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>88</td>\n",
       "      <td>The African Queen</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Adventure', u' Romance', u' War']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>89</td>\n",
       "      <td>Stagecoach</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Adventure', u' Western']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>90</td>\n",
       "      <td>Mutiny on the Bounty</td>\n",
       "      <td>2</td>\n",
       "      <td>[u' Adventure', u' Drama', u' History']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>91</td>\n",
       "      <td>The Maltese Falcon</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Drama', u' Film-Noir', u' Mystery']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>92</td>\n",
       "      <td>A Clockwork Orange</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Crime', u' Drama', u' Sci-Fi']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93</td>\n",
       "      <td>Taxi Driver</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>94</td>\n",
       "      <td>Wuthering Heights</td>\n",
       "      <td>1</td>\n",
       "      <td>[u' Drama', u' Romance']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>95</td>\n",
       "      <td>Double Indemnity</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Crime', u' Drama', u' Film-Noir', u' Thril...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>96</td>\n",
       "      <td>Rebel Without a Cause</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Drama']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>97</td>\n",
       "      <td>Rear Window</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Mystery', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>98</td>\n",
       "      <td>The Third Man</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Film-Noir', u' Mystery', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>99</td>\n",
       "      <td>North by Northwest</td>\n",
       "      <td>0</td>\n",
       "      <td>[u' Mystery', u' Thriller']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100</td>\n",
       "      <td>Yankee Doodle Dandy</td>\n",
       "      <td>3</td>\n",
       "      <td>[u' Biography', u' Drama', u' Musical']</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    rank                                              title  cluster  \\\n",
       "4      1                                      The Godfather        4   \n",
       "0      2                           The Shawshank Redemption        0   \n",
       "3      3                                   Schindler's List        3   \n",
       "1      4                                        Raging Bull        1   \n",
       "0      5                                         Casablanca        0   \n",
       "3      6                    One Flew Over the Cuckoo's Nest        3   \n",
       "3      7                                 Gone with the Wind        3   \n",
       "1      8                                       Citizen Kane        1   \n",
       "1      9                                   The Wizard of Oz        1   \n",
       "3     10                                            Titanic        3   \n",
       "2     11                                 Lawrence of Arabia        2   \n",
       "4     12                             The Godfather: Part II        4   \n",
       "0     13                                             Psycho        0   \n",
       "3     14                                       Sunset Blvd.        3   \n",
       "1     15                                            Vertigo        1   \n",
       "0     16                                  On the Waterfront        0   \n",
       "1     17                                       Forrest Gump        1   \n",
       "1     18                                 The Sound of Music        1   \n",
       "0     19                                    West Side Story        0   \n",
       "2     20                                          Star Wars        2   \n",
       "0     21                         E.T. the Extra-Terrestrial        0   \n",
       "0     22                              2001: A Space Odyssey        0   \n",
       "0     23                           The Silence of the Lambs        0   \n",
       "0     24                                          Chinatown        0   \n",
       "2     25                       The Bridge on the River Kwai        2   \n",
       "3     26                                Singin' in the Rain        3   \n",
       "3     27                              It's a Wonderful Life        3   \n",
       "3     28                                   Some Like It Hot        3   \n",
       "1     29                                       12 Angry Men        1   \n",
       "2     30  Dr. Strangelove or: How I Learned to Stop Worr...        2   \n",
       "..   ...                                                ...      ...   \n",
       "4     71                                           Rain Man        4   \n",
       "1     72                                         Annie Hall        1   \n",
       "1     73                                      Out of Africa        1   \n",
       "3     74                                  Good Will Hunting        3   \n",
       "1     75                                Terms of Endearment        1   \n",
       "1     76                                            Tootsie        1   \n",
       "0     77                                              Fargo        0   \n",
       "4     78                                              Giant        4   \n",
       "4     79                                The Grapes of Wrath        4   \n",
       "0     80                                              Shane        0   \n",
       "1     81                                     The Green Mile        1   \n",
       "1     82                 Close Encounters of the Third Kind        1   \n",
       "1     83                                            Network        1   \n",
       "3     84                                          Nashville        3   \n",
       "1     85                                       The Graduate        1   \n",
       "0     86                                  American Graffiti        0   \n",
       "0     87                                       Pulp Fiction        0   \n",
       "2     88                                  The African Queen        2   \n",
       "2     89                                         Stagecoach        2   \n",
       "2     90                               Mutiny on the Bounty        2   \n",
       "0     91                                 The Maltese Falcon        0   \n",
       "3     92                                 A Clockwork Orange        3   \n",
       "0     93                                        Taxi Driver        0   \n",
       "1     94                                  Wuthering Heights        1   \n",
       "0     95                                   Double Indemnity        0   \n",
       "0     96                              Rebel Without a Cause        0   \n",
       "3     97                                        Rear Window        3   \n",
       "0     98                                      The Third Man        0   \n",
       "0     99                                 North by Northwest        0   \n",
       "3    100                                Yankee Doodle Dandy        3   \n",
       "\n",
       "                                                genre  \n",
       "4                              [u' Crime', u' Drama']  \n",
       "0                              [u' Crime', u' Drama']  \n",
       "3             [u' Biography', u' Drama', u' History']  \n",
       "1               [u' Biography', u' Drama', u' Sport']  \n",
       "0                   [u' Drama', u' Romance', u' War']  \n",
       "3                                         [u' Drama']  \n",
       "3                   [u' Drama', u' Romance', u' War']  \n",
       "1                            [u' Drama', u' Mystery']  \n",
       "1   [u' Adventure', u' Family', u' Fantasy', u' Mu...  \n",
       "3                            [u' Drama', u' Romance']  \n",
       "2   [u' Adventure', u' Biography', u' Drama', u' H...  \n",
       "4                              [u' Crime', u' Drama']  \n",
       "0             [u' Horror', u' Mystery', u' Thriller']  \n",
       "3                          [u' Drama', u' Film-Noir']  \n",
       "1            [u' Mystery', u' Romance', u' Thriller']  \n",
       "0                              [u' Crime', u' Drama']  \n",
       "1                            [u' Drama', u' Romance']  \n",
       "1   [u' Biography', u' Drama', u' Family', u' Musi...  \n",
       "0   [u' Crime', u' Drama', u' Musical', u' Romance...  \n",
       "2   [u' Action', u' Adventure', u' Fantasy', u' Sc...  \n",
       "0             [u' Adventure', u' Family', u' Sci-Fi']  \n",
       "0                           [u' Mystery', u' Sci-Fi']  \n",
       "0                [u' Crime', u' Drama', u' Thriller']  \n",
       "0              [u' Drama', u' Mystery', u' Thriller']  \n",
       "2                 [u' Adventure', u' Drama', u' War']  \n",
       "3              [u' Comedy', u' Musical', u' Romance']  \n",
       "3                [u' Drama', u' Family', u' Fantasy']  \n",
       "3                                        [u' Comedy']  \n",
       "1                                         [u' Drama']  \n",
       "2                               [u' Comedy', u' War']  \n",
       "..                                                ...  \n",
       "4                                         [u' Drama']  \n",
       "1                [u' Comedy', u' Drama', u' Romance']  \n",
       "1             [u' Biography', u' Drama', u' Romance']  \n",
       "3                                         [u' Drama']  \n",
       "1                             [u' Comedy', u' Drama']  \n",
       "1                [u' Comedy', u' Drama', u' Romance']  \n",
       "0                [u' Crime', u' Drama', u' Thriller']  \n",
       "4                            [u' Drama', u' Romance']  \n",
       "4                                         [u' Drama']  \n",
       "0               [u' Drama', u' Romance', u' Western']  \n",
       "1    [u' Crime', u' Drama', u' Fantasy', u' Mystery']  \n",
       "1                             [u' Drama', u' Sci-Fi']  \n",
       "1                                         [u' Drama']  \n",
       "3                              [u' Drama', u' Music']  \n",
       "1                [u' Comedy', u' Drama', u' Romance']  \n",
       "0                             [u' Comedy', u' Drama']  \n",
       "0                [u' Crime', u' Drama', u' Thriller']  \n",
       "2               [u' Adventure', u' Romance', u' War']  \n",
       "2                        [u' Adventure', u' Western']  \n",
       "2             [u' Adventure', u' Drama', u' History']  \n",
       "0             [u' Drama', u' Film-Noir', u' Mystery']  \n",
       "3                  [u' Crime', u' Drama', u' Sci-Fi']  \n",
       "0                              [u' Crime', u' Drama']  \n",
       "1                            [u' Drama', u' Romance']  \n",
       "0   [u' Crime', u' Drama', u' Film-Noir', u' Thril...  \n",
       "0                                         [u' Drama']  \n",
       "3                         [u' Mystery', u' Thriller']  \n",
       "0          [u' Film-Noir', u' Mystery', u' Thriller']  \n",
       "0                         [u' Mystery', u' Thriller']  \n",
       "3             [u' Biography', u' Drama', u' Musical']  \n",
       "\n",
       "[100 rows x 4 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame #聚类结果"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#谱系聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RERFR2Qd4m6TfSroDuAD4D+AcYJWyzONS4DDbLwBntyg/B1hL0r3Al6iyNZo5D7gXmF5e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\nLczMzMzMzMysWfr/a1xd0aFTkqcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x21b01908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import ward, dendrogram\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "linkage_matrix = ward(dist) #通过ward法构建矩阵\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15,20))\n",
    "ax = dendrogram(linkage_matrix, orientation='right', labels=titles)\n",
    "\n",
    "plt.tick_params(axis= 'x',          \n",
    "                which='both',      \n",
    "                bottom='off',      \n",
    "                top='off',         \n",
    "                labelbottom='off')\n",
    "\n",
    "plt.tight_layout() #紧凑布局\n",
    "\n",
    "#保存图像\n",
    "plt.savefig('ward_clusters.png', dpi=200) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LDA主题建模"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "LDA主题建模需要并不依赖TF-IDF模型，所以需要重新进行数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#分词\n",
    "import string\n",
    "def strip_proppers(text):\n",
    "    # first tokenize by sentence, then by word to ensure that punctuation is caught as it's own token\n",
    "    tokens = [word for sent in nltk.sent_tokenize(text) for word in nltk.word_tokenize(sent) if word.islower()]\n",
    "    return \"\".join([\" \"+i if not i.startswith(\"'\") and i not in string.punctuation else i for i in tokens]).strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#文本准备\n",
    "from gensim import corpora, models, similarities\n",
    "\n",
    "#remove proper names\n",
    "preprocess = [strip_proppers(doc) for doc in synopses]\n",
    "\n",
    "tokenized_text = [tokenize_and_stem(text) for text in preprocess]\n",
    "\n",
    "texts = [[word for word in text if word not in stopwords] for text in tokenized_text]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#词典和语料库准备\n",
    "dictionary = corpora.Dictionary(texts) #构造词典\n",
    "dictionary.filter_extremes(no_below=1, no_above=0.8)#去高频词\n",
    "\n",
    "corpus = [dictionary.doc2bow(text) for text in texts] #构造语料库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2min 55s\n"
     ]
    }
   ],
   "source": [
    "#训练一个LDA模型\n",
    "%time lda = models.LdaModel(corpus, num_topics=5, id2word=dictionary, update_every=5, chunksize=10000, passes=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(3, 0.99856435945125999)]\n"
     ]
    }
   ],
   "source": [
    "print(lda[corpus[0]])#打印第一个文档的主题建模结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "topics = lda.print_topics(5, num_words=20)#结果中的主题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'0.006*kill + 0.006*take + 0.005*return + 0.005*back + 0.005*shark + 0.004*home + 0.004*befor + 0.004*polic + 0.004*arriv + 0.004*tri + 0.004*find + 0.004*famili + 0.004*discov + 0.003*order + 0.003*one + 0.003*father + 0.003*attack + 0.003*make + 0.003*command + 0.003*learn',\n",
       " u'0.007*kill + 0.005*tell + 0.005*famili + 0.005*man + 0.005*leav + 0.005*find + 0.004*friend + 0.004*return + 0.004*life + 0.004*back + 0.004*order + 0.004*fight + 0.004*take + 0.003*arriv + 0.003*first + 0.003*make + 0.003*prison + 0.003*way + 0.003*meet + 0.003*ask',\n",
       " u'0.006*kill + 0.005*find + 0.005*take + 0.005*return + 0.004*man + 0.004*time + 0.004*say + 0.004*tell + 0.004*vote + 0.004*ask + 0.004*home + 0.004*befor + 0.004*friend + 0.004*one + 0.003*make + 0.003*night + 0.003*onli + 0.003*begin + 0.003*love + 0.003*murder',\n",
       " u'0.006*leav + 0.005*get + 0.005*tell + 0.005*make + 0.004*home + 0.004*take + 0.004*love + 0.004*tri + 0.004*kill + 0.004*arriv + 0.004*find + 0.004*go + 0.004*back + 0.004*fight + 0.003*day + 0.003*call + 0.003*father + 0.003*see + 0.003*end + 0.003*run',\n",
       " u'0.007*leav + 0.006*return + 0.006*take + 0.005*tell + 0.005*find + 0.005*apart + 0.005*film + 0.004*kill + 0.004*night + 0.004*becom + 0.004*tri + 0.004*friend + 0.004*make + 0.004*man + 0.004*get + 0.003*ask + 0.003*see + 0.003*two + 0.003*father + 0.003*discov']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topics #主题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "topics_matrix = lda.show_topics(formatted=False, num_words=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "topics_matrix = np.array(topics_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[u'0.00593728051897', u'kill'],\n",
       "        [u'0.0055825257252', u'take'],\n",
       "        [u'0.00496062793487', u'return'],\n",
       "        [u'0.00483481306431', u'back'],\n",
       "        [u'0.00480556317119', u'shark'],\n",
       "        [u'0.0044004127217', u'home'],\n",
       "        [u'0.00419618701223', u'befor'],\n",
       "        [u'0.0041661085672', u'polic'],\n",
       "        [u'0.00394552565961', u'arriv'],\n",
       "        [u'0.00388931191125', u'tri'],\n",
       "        [u'0.00384788046479', u'find'],\n",
       "        [u'0.00367382009423', u'famili'],\n",
       "        [u'0.00358706714583', u'discov'],\n",
       "        [u'0.00349972303922', u'order'],\n",
       "        [u'0.00346444201506', u'one'],\n",
       "        [u'0.00345468490397', u'father'],\n",
       "        [u'0.00332564867337', u'attack'],\n",
       "        [u'0.00332556499353', u'make'],\n",
       "        [u'0.00315155482136', u'command'],\n",
       "        [u'0.00311890645064', u'learn']],\n",
       "\n",
       "       [[u'0.00715837199668', u'kill'],\n",
       "        [u'0.00535375220484', u'tell'],\n",
       "        [u'0.00499557447521', u'famili'],\n",
       "        [u'0.00499304368397', u'man'],\n",
       "        [u'0.00493849070503', u'leav'],\n",
       "        [u'0.00493790942029', u'find'],\n",
       "        [u'0.0044049685848', u'friend'],\n",
       "        [u'0.00413480100702', u'return'],\n",
       "        [u'0.00388676137211', u'life'],\n",
       "        [u'0.00375299605718', u'back'],\n",
       "        [u'0.0037346082665', u'order'],\n",
       "        [u'0.00362266336055', u'fight'],\n",
       "        [u'0.00360034092823', u'take'],\n",
       "        [u'0.00342864925198', u'arriv'],\n",
       "        [u'0.00340961506156', u'first'],\n",
       "        [u'0.00337238361536', u'make'],\n",
       "        [u'0.00331432820091', u'prison'],\n",
       "        [u'0.00330795658758', u'way'],\n",
       "        [u'0.00322158691844', u'meet'],\n",
       "        [u'0.0032070297038', u'ask']],\n",
       "\n",
       "       [[u'0.00582119174495', u'kill'],\n",
       "        [u'0.00487970771401', u'find'],\n",
       "        [u'0.00469944393744', u'take'],\n",
       "        [u'0.00455596223554', u'return'],\n",
       "        [u'0.00431860545204', u'man'],\n",
       "        [u'0.00423258411918', u'time'],\n",
       "        [u'0.00405579924199', u'say'],\n",
       "        [u'0.00392344772473', u'tell'],\n",
       "        [u'0.00380786413858', u'vote'],\n",
       "        [u'0.00378255335825', u'ask'],\n",
       "        [u'0.00365104324901', u'home'],\n",
       "        [u'0.00362688414882', u'befor'],\n",
       "        [u'0.00359782953736', u'friend'],\n",
       "        [u'0.00353371850773', u'one'],\n",
       "        [u'0.003279171247', u'make'],\n",
       "        [u'0.00317625654581', u'night'],\n",
       "        [u'0.00317587040334', u'onli'],\n",
       "        [u'0.00315461809077', u'begin'],\n",
       "        [u'0.00314843692965', u'love'],\n",
       "        [u'0.003077782692', u'murder']],\n",
       "\n",
       "       [[u'0.00593016542098', u'leav'],\n",
       "        [u'0.00497057803933', u'get'],\n",
       "        [u'0.00465146672243', u'tell'],\n",
       "        [u'0.0046508929421', u'make'],\n",
       "        [u'0.00449204369148', u'home'],\n",
       "        [u'0.00449174202671', u'take'],\n",
       "        [u'0.00433208452955', u'love'],\n",
       "        [u'0.00433200196021', u'tri'],\n",
       "        [u'0.00433111570668', u'kill'],\n",
       "        [u'0.00401206970286', u'arriv'],\n",
       "        [u'0.00401152264537', u'find'],\n",
       "        [u'0.00393269577179', u'go'],\n",
       "        [u'0.00393205581092', u'back'],\n",
       "        [u'0.00369195142786', u'fight'],\n",
       "        [u'0.00337326997872', u'day'],\n",
       "        [u'0.00337307669527', u'call'],\n",
       "        [u'0.00337248152121', u'father'],\n",
       "        [u'0.00321271752906', u'see'],\n",
       "        [u'0.00321247537524', u'end'],\n",
       "        [u'0.00305322431739', u'run']],\n",
       "\n",
       "       [[u'0.00660000285972', u'leav'],\n",
       "        [u'0.00612034115546', u'return'],\n",
       "        [u'0.00551177277551', u'take'],\n",
       "        [u'0.00502148111266', u'tell'],\n",
       "        [u'0.00476244014681', u'find'],\n",
       "        [u'0.00452672790397', u'apart'],\n",
       "        [u'0.0045097138479', u'film'],\n",
       "        [u'0.00449296522362', u'kill'],\n",
       "        [u'0.00375846391583', u'night'],\n",
       "        [u'0.00375102222556', u'becom'],\n",
       "        [u'0.00372537320405', u'tri'],\n",
       "        [u'0.00370219814976', u'friend'],\n",
       "        [u'0.00357074557682', u'make'],\n",
       "        [u'0.00355615429764', u'man'],\n",
       "        [u'0.00350753536498', u'get'],\n",
       "        [u'0.00344019524237', u'ask'],\n",
       "        [u'0.00341920302192', u'see'],\n",
       "        [u'0.00338876374863', u'two'],\n",
       "        [u'0.00336807121248', u'father'],\n",
       "        [u'0.00335008691386', u'discov']]], \n",
       "      dtype='<U32')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topics_matrix #主题矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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