clustering_code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from gensim import models\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.cluster import KMeans\n",
    "import pandas as pd\n",
    "\n",
    "# ko_model = models.fasttext.load_facebook_model('./wiki.ko.bin')\n",
    "# Load the FastText model\n",
    "ko_model = models.fasttext.load_facebook_model('./cc.ko.300.bin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "words_list =  ['네트워크 통합', '전산장비 유지보수', '정보 통신', '공급 유지보수', '빅데이터 서비스', '서비스 서비스', '연결 대상', '소프트웨어 판매', '서비스 비즈니스', '상호 변경', '네트워크 보안', '서비스 인프라', '금융 데이터', '소프트웨어 공급', '스마트카 서비스', '경쟁력 강화', '시스템 공급', '네트워크 설계', '인터넷 유해', '장비 공급', '소프트웨어 플랫폼', '컨텐츠 서비스', '가상계좌 중계서비스', '증서 보관서비스', '휴대폰 증서', '휴대폰 증서 보관서비스', '시스템 설치', '영역 확장', '대상 보유', '연결 대상 보유', '상업 총판', '판매 소프트웨어', '안정 운영', '인프라 서비스', '운영 서비스', '장비 제조', '통신사 고객', '자회사 평가', '자회사 평가 정보', '평가 정보', '시스템 통합', '산업 전반', '제조 판매', '서비스 시작', '고객 성공', '고객 성공 영역', '디지털 워크플레이스', '디지털 워크플레이스 영역', '성공 영역', '워크플레이스 영역']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 임베딩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['네트워크 통합',\n",
       " '전산장비 유지보수',\n",
       " '정보 통신',\n",
       " '공급 유지보수',\n",
       " '빅데이터 서비스',\n",
       " '서비스 서비스',\n",
       " '연결 대상',\n",
       " '소프트웨어 판매',\n",
       " '서비스 비즈니스',\n",
       " '상호 변경',\n",
       " '네트워크 보안',\n",
       " '서비스 인프라',\n",
       " '금융 데이터',\n",
       " '소프트웨어 공급',\n",
       " '스마트카 서비스',\n",
       " '경쟁력 강화',\n",
       " '시스템 공급',\n",
       " '네트워크 설계',\n",
       " '인터넷 유해',\n",
       " '장비 공급',\n",
       " '소프트웨어 플랫폼',\n",
       " '컨텐츠 서비스',\n",
       " '가상계좌 중계서비스',\n",
       " '증서 보관서비스',\n",
       " '휴대폰 증서',\n",
       " '휴대폰 증서 보관서비스',\n",
       " '시스템 설치',\n",
       " '영역 확장',\n",
       " '대상 보유',\n",
       " '연결 대상 보유',\n",
       " '상업 총판',\n",
       " '판매 소프트웨어',\n",
       " '안정 운영',\n",
       " '인프라 서비스',\n",
       " '운영 서비스',\n",
       " '장비 제조',\n",
       " '통신사 고객',\n",
       " '자회사 평가',\n",
       " '자회사 평가 정보',\n",
       " '평가 정보',\n",
       " '시스템 통합',\n",
       " '산업 전반',\n",
       " '제조 판매',\n",
       " '서비스 시작',\n",
       " '고객 성공',\n",
       " '고객 성공 영역',\n",
       " '디지털 워크플레이스',\n",
       " '디지털 워크플레이스 영역',\n",
       " '성공 영역',\n",
       " '워크플레이스 영역']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Words to be embedded and clustered\n",
    "# Get the word embeddings\n",
    "embeddings = np.array([ko_model.wv[word] for word in words_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50, 300)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embeddings.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.family'] = 'AppleGothic'\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# t-sne, KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/leewonseok/anaconda3/envs/vvv/lib/python3.8/site-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster 1: ['빅데이터 서비스', '서비스 서비스', '서비스 비즈니스', '상호 변경', '서비스 인프라', '시스템 공급', '장비 공급', '컨텐츠 서비스', '시스템 설치', '판매 소프트웨어', '안정 운영', '운영 서비스', '서비스 시작']\n",
      "Cluster 2: ['인프라 서비스', '자회사 평가', '자회사 평가 정보']\n",
      "Cluster 3: ['연결 대상', '가상계좌 중계서비스', '통신사 고객', '성공 영역']\n",
      "Cluster 4: ['소프트웨어 판매', '소프트웨어 공급', '스마트카 서비스', '소프트웨어 플랫폼', '영역 확장', '워크플레이스 영역']\n",
      "Cluster 5: ['네트워크 통합', '네트워크 보안', '네트워크 설계']\n",
      "Cluster 6: ['정보 통신', '상업 총판', '디지털 워크플레이스', '디지털 워크플레이스 영역']\n",
      "Cluster 7: ['금융 데이터', '경쟁력 강화', '인터넷 유해', '증서 보관서비스', '휴대폰 증서', '휴대폰 증서 보관서비스', '연결 대상 보유', '장비 제조', '평가 정보', '산업 전반', '제조 판매', '고객 성공', '고객 성공 영역']\n",
      "Cluster 8: ['전산장비 유지보수', '공급 유지보수', '대상 보유', '시스템 통합']\n"
     ]
    }
   ],
   "source": [
    "# Assuming you have obtained the embeddings and words before this point\n",
    "# embeddings = ...\n",
    "# words = ...\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "# Reduce dimensionality using t-SNE\n",
    "tsne = TSNE(n_components=2, random_state=42)\n",
    "embeddings_2d = tsne.fit_transform(embeddings)\n",
    "\n",
    "# Calculate cosine similarity matrix\n",
    "cosine_sim = cosine_similarity(embeddings_2d)\n",
    "\n",
    "# Perform clustering using KMeans\n",
    "num_clusters = 8\n",
    "kmeans = KMeans(n_clusters=num_clusters, random_state=42)\n",
    "cluster_labels = kmeans.fit_predict(cosine_sim)\n",
    "\n",
    "# Create a dictionary to store clustered words\n",
    "clustered_words = {i: [] for i in range(num_clusters)}\n",
    "\n",
    "# Populate the dictionary with words in each cluster\n",
    "for i, word in enumerate(words_list):\n",
    "    cluster_idx = cluster_labels[i]\n",
    "    clustered_words[cluster_idx].append(word)\n",
    "\n",
    "# Visualize the clustered embeddings and annotate words\n",
    "plt.figure(figsize=(20, 20))\n",
    "for i in range(num_clusters):\n",
    "    x = embeddings_2d[cluster_labels == i, 0]\n",
    "    y = embeddings_2d[cluster_labels == i, 1]\n",
    "    plt.scatter(x, y, label=f'Cluster {i+1}')\n",
    "\n",
    "    for word in clustered_words[i]:\n",
    "        idx = words_list.index(word)\n",
    "        plt.annotate(word, (embeddings_2d[idx, 0], embeddings_2d[idx, 1]), textcoords=\"offset points\", xytext=(0, 5), ha='center')\n",
    "\n",
    "plt.title('Word Embeddings Visualization with Clustering')\n",
    "plt.xlabel('Dimension 1')\n",
    "plt.ylabel('Dimension 2')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# Print the words in each cluster\n",
    "for i in range(num_clusters):\n",
    "    print(f\"Cluster {i+1}: {clustered_words[i]}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# HDBSCAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/leewonseok/anaconda3/envs/vvv/lib/python3.8/site-packages/pacmap/pacmap.py:819: UserWarning: Warning: random state is set to 42\n",
      "  warnings.warn(f'Warning: random state is set to {_RANDOM_STATE}')\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x3000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster -1: ['전산장비 유지보수', '연결 대상', '상호 변경', '인터넷 유해', '장비 공급', '장비 제조', '통신사 고객', '자회사 평가', '제조 판매', '디지털 워크플레이스 영역', '성공 영역']\n",
      "Cluster 0: ['소프트웨어 판매', '소프트웨어 공급', '스마트카 서비스']\n",
      "Cluster 1: ['서비스 인프라', '시스템 공급', '시스템 설치', '판매 소프트웨어', '안정 운영']\n",
      "Cluster 2: ['서비스 비즈니스', '금융 데이터', '휴대폰 증서']\n",
      "Cluster 3: ['경쟁력 강화', '컨텐츠 서비스', '휴대폰 증서 보관서비스', '운영 서비스', '평가 정보', '산업 전반', '고객 성공', '고객 성공 영역']\n",
      "Cluster 4: ['공급 유지보수', '빅데이터 서비스', '서비스 서비스', '증서 보관서비스', '연결 대상 보유', '워크플레이스 영역']\n",
      "Cluster 5: ['정보 통신', '네트워크 설계', '영역 확장', '대상 보유', '상업 총판', '인프라 서비스', '자회사 평가 정보', '시스템 통합', '디지털 워크플레이스']\n",
      "Cluster 6: ['네트워크 통합', '네트워크 보안', '소프트웨어 플랫폼', '가상계좌 중계서비스', '서비스 시작']\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import hdbscan\n",
    "import pacmap\n",
    "\n",
    "# t-SNE 모델 설정\n",
    "pac = pacmap.PaCMAP(n_components=2, n_neighbors=None, MN_ratio=0.5, FP_ratio=2.0, random_state=42) \n",
    "pac_embeddings = pac.fit_transform(embeddings, init=\"pca\")\n",
    "\n",
    "# HDBSCAN 모델 설정\n",
    "hdbscan_model = hdbscan.HDBSCAN(min_cluster_size=2, gen_min_span_tree=True)\n",
    "\n",
    "# HDBSCAN을 사용하여 클러스터링\n",
    "hdbscan_labels = hdbscan_model.fit_predict(pac_embeddings)\n",
    "\n",
    "# Visualize the clustered embeddings and store the coordinates\n",
    "plt.figure(figsize=(30, 30))\n",
    "for cluster_id in np.unique(hdbscan_labels):\n",
    "    x = pac_embeddings[hdbscan_labels == cluster_id, 0]\n",
    "    y = pac_embeddings[hdbscan_labels == cluster_id, 1]\n",
    "    plt.scatter(x, y, label=f'Cluster {cluster_id}', alpha=0.7)\n",
    "\n",
    "for i, word in enumerate(words_list):\n",
    "    plt.annotate(word, (pac_embeddings[i, 0], pac_embeddings[i, 1]), textcoords=\"offset points\", xytext=(0, 5), ha='center')\n",
    "\n",
    "plt.title('Word Embeddings Visualization with HDBSCAN Clustering')\n",
    "plt.xlabel('Dimension 1')\n",
    "plt.ylabel('Dimension 2')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# 클러스터별로 단어 리스트 저장\n",
    "cluster_word_lists = {}\n",
    "for cluster_id in np.unique(hdbscan_labels):\n",
    "    cluster_words = [word for i, word in enumerate(words_list) if hdbscan_labels[i] == cluster_id]\n",
    "    cluster_word_lists[f'Cluster {cluster_id}'] = cluster_words\n",
    "    print(f'Cluster {cluster_id}: {cluster_words}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DBSCAN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cluster -1: ['네트워크 통합', '네트워크 보안', '네트워크 설계', '장비 공급', '시스템 통합', '성공 영역']\n",
      "Cluster 0: ['전산장비 유지보수', '정보 통신', '공급 유지보수', '빅데이터 서비스', '서비스 서비스', '연결 대상', '소프트웨어 판매', '서비스 비즈니스', '상호 변경', '서비스 인프라', '금융 데이터', '소프트웨어 공급', '스마트카 서비스', '경쟁력 강화', '시스템 공급', '인터넷 유해', '소프트웨어 플랫폼', '컨텐츠 서비스', '가상계좌 중계서비스', '증서 보관서비스', '휴대폰 증서', '휴대폰 증서 보관서비스', '시스템 설치', '영역 확장', '대상 보유', '연결 대상 보유', '상업 총판', '판매 소프트웨어', '안정 운영', '인프라 서비스', '운영 서비스', '장비 제조', '통신사 고객', '자회사 평가', '자회사 평가 정보', '평가 정보', '산업 전반', '제조 판매', '서비스 시작', '고객 성공', '고객 성공 영역', '디지털 워크플레이스', '디지털 워크플레이스 영역', '워크플레이스 영역']\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "# Assume you have obtained embeddings and words\n",
    "# embeddings = ...\n",
    "# words = ...\n",
    "\n",
    "# Reduce dimensionality using t-SNE\n",
    "tsne = TSNE(n_components=2, random_state=42)\n",
    "embeddings_2d = tsne.fit_transform(embeddings)\n",
    "\n",
    "# Perform DBSCAN clustering\n",
    "dbscan_model = DBSCAN(eps=0.76, min_samples=4)\n",
    "cluster_labels = dbscan_model.fit_predict(embeddings_2d)\n",
    "\n",
    "# Create a dictionary to store clustered words\n",
    "clustered_words = {i: [] for i in np.unique(cluster_labels)}\n",
    "\n",
    "# Populate the dictionary with words in each cluster\n",
    "for i, word in enumerate(words_list):\n",
    "    cluster_idx = cluster_labels[i]\n",
    "    clustered_words[cluster_idx].append(word)\n",
    "\n",
    "# Visualize the clustered embeddings and annotate words\n",
    "plt.figure(figsize=(20, 20))\n",
    "for cluster_idx in clustered_words:\n",
    "    x = embeddings_2d[cluster_labels == cluster_idx, 0]\n",
    "    y = embeddings_2d[cluster_labels == cluster_idx, 1]\n",
    "    plt.scatter(x, y, label=f'Cluster {cluster_idx}', alpha=0.7)\n",
    "\n",
    "    for word in clustered_words[cluster_idx]:\n",
    "        idx = words_list.index(word)\n",
    "        plt.annotate(word, (embeddings_2d[idx, 0], embeddings_2d[idx, 1]), textcoords=\"offset points\", xytext=(0, 5), ha='center')\n",
    "\n",
    "plt.title('Word Embeddings Visualization with DBSCAN Clustering')\n",
    "plt.xlabel('Dimension 1')\n",
    "plt.ylabel('Dimension 2')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# Print the words in each cluster\n",
    "for cluster_idx in clustered_words:\n",
    "    print(f\"Cluster {cluster_idx}: {clustered_words[cluster_idx]}\")\n"
   ]
  }
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