{"id":1175908,"date":"2025-01-15T17:38:17","date_gmt":"2025-01-15T09:38:17","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1175908.html"},"modified":"2025-01-15T17:38:19","modified_gmt":"2025-01-15T09:38:19","slug":"%e5%a6%82%e4%bd%95%e5%8e%bb%e6%8e%89python%e7%9a%84%e5%81%9c%e7%94%a8%e8%af%8d","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1175908.html","title":{"rendered":"\u5982\u4f55\u53bb\u6389python\u7684\u505c\u7528\u8bcd"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25111226\/b03e54a3-89cf-4aa5-913f-a7dc06b6b888.webp\" alt=\"\u5982\u4f55\u53bb\u6389python\u7684\u505c\u7528\u8bcd\" \/><\/p>\n<p><p> <strong>\u4f7f\u7528NLTK\u5e93\u3001\u4f7f\u7528SpaCy\u5e93\u3001\u4f7f\u7528gensim\u5e93\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868<\/strong>\u3002\u5176\u4e2d\uff0c\u4f7f\u7528NLTK\u5e93\u662f\u4e00\u79cd\u5e38\u89c1\u4e14\u7b80\u4fbf\u7684\u65b9\u6cd5\u3002NLTK\uff08Natural Language Toolkit\uff09\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684Python\u5e93\uff0c\u53ef\u4ee5\u7528\u4e8e\u5904\u7406\u548c\u5206\u6790\u81ea\u7136\u8bed\u8a00\u6570\u636e\u3002\u901a\u8fc7NLTK\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u5e76\u5bfc\u5165NLTK\u5e93\uff0c\u7136\u540e\u4e0b\u8f7d\u505c\u7528\u8bcd\u5217\u8868\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u6587\u672c\u8fdb\u884c\u5206\u8bcd\u64cd\u4f5c\uff0c\u5e76\u53bb\u9664\u505c\u7528\u8bcd\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u7684\u6b65\u9aa4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import nltk<\/p>\n<p>from nltk.corpus import stopwords<\/p>\n<p>from nltk.tokenize import word_tokenize<\/p>\n<h2><strong>\u4e0b\u8f7d\u505c\u7528\u8bcd\u5217\u8868<\/strong><\/h2>\n<p>nltk.download(&#39;stopwords&#39;)<\/p>\n<p>nltk.download(&#39;punkt&#39;)<\/p>\n<h2><strong>\u83b7\u53d6\u82f1\u8bed\u7684\u505c\u7528\u8bcd\u5217\u8868<\/strong><\/h2>\n<p>stop_words = set(stopwords.words(&#39;english&#39;))<\/p>\n<h2><strong>\u793a\u4f8b\u6587\u672c<\/strong><\/h2>\n<p>text = &quot;This is a sample sentence, showing off the stop words filtration.&quot;<\/p>\n<h2><strong>\u5206\u8bcd<\/strong><\/h2>\n<p>word_tokens = word_tokenize(text)<\/p>\n<h2><strong>\u53bb\u9664\u505c\u7528\u8bcd<\/strong><\/h2>\n<p>filtered_sentence = [w for w in word_tokens if not w.lower() in stop_words]<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5bfc\u5165\u4e86\u6240\u9700\u7684NLTK\u6a21\u5757\uff0c\u5e76\u4e0b\u8f7d\u4e86\u505c\u7528\u8bcd\u5217\u8868\u548cpunkt\u5206\u8bcd\u5668\u3002\u7136\u540e\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u6bb5\u793a\u4f8b\u6587\u672c\uff0c\u5e76\u5c06\u5176\u8fdb\u884c\u5206\u8bcd\u64cd\u4f5c\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u901a\u8fc7\u5217\u8868\u63a8\u5bfc\u5f0f\u5c06\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u53bb\u9664\uff0c\u5f97\u5230\u8fc7\u6ee4\u540e\u7684\u53e5\u5b50\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528NLTK\u5e93\u53bb\u9664\u505c\u7528\u8bcd<\/h3>\n<\/p>\n<p><p>NLTK\u5e93\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u548c\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165NLTK\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u4f7f\u7528NLTK\u5e93\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5b89\u88c5NLTK\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install nltk<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165NLTK\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import nltk<\/p>\n<p>from nltk.corpus import stopwords<\/p>\n<p>from nltk.tokenize import word_tokenize<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u4e0b\u8f7d\u505c\u7528\u8bcd\u5217\u8868<\/h4>\n<\/p>\n<p><p>NLTK\u5e93\u63d0\u4f9b\u4e86\u591a\u79cd\u8bed\u8a00\u7684\u505c\u7528\u8bcd\u5217\u8868\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u9700\u8981\u4e0b\u8f7d\u76f8\u5e94\u7684\u505c\u7528\u8bcd\u5217\u8868\u3002\u4ee5\u4e0b\u662f\u4e0b\u8f7d\u82f1\u8bed\u505c\u7528\u8bcd\u5217\u8868\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">nltk.download(&#39;stopwords&#39;)<\/p>\n<p>nltk.download(&#39;punkt&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u83b7\u53d6\u505c\u7528\u8bcd\u5217\u8868<\/h4>\n<\/p>\n<p><p>\u4e0b\u8f7d\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u83b7\u53d6\u505c\u7528\u8bcd\u5217\u8868\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">stop_words = set(stopwords.words(&#39;english&#39;))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u5206\u8bcd\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>\u5728\u53bb\u9664\u505c\u7528\u8bcd\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5c06\u6587\u672c\u8fdb\u884c\u5206\u8bcd\u64cd\u4f5c\u3002\u53ef\u4ee5\u4f7f\u7528NLTK\u5e93\u63d0\u4f9b\u7684word_tokenize\u51fd\u6570\u8fdb\u884c\u5206\u8bcd\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">text = &quot;This is a sample sentence, showing off the stop words filtration.&quot;<\/p>\n<p>word_tokens = word_tokenize(text)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>5\u3001\u53bb\u9664\u505c\u7528\u8bcd<\/h4>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5217\u8868\u63a8\u5bfc\u5f0f\u5c06\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u53bb\u9664\uff0c\u5f97\u5230\u8fc7\u6ee4\u540e\u7684\u53e5\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">filtered_sentence = [w for w in word_tokens if not w.lower() in stop_words]<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528SpaCy\u5e93\u53bb\u9664\u505c\u7528\u8bcd<\/h3>\n<\/p>\n<p><p>\u9664\u4e86NLTK\u5e93\uff0cSpaCy\u4e5f\u662f\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165SpaCy\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u4f7f\u7528SpaCy\u5e93\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5b89\u88c5SpaCy\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install spacy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u8fd8\u9700\u8981\u4e0b\u8f7dSpaCy\u7684\u6a21\u578b\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u4e0b\u8f7d\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">python -m spacy download en_core_web_sm<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u548c\u4e0b\u8f7d\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165SpaCy\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import spacy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u52a0\u8f7d\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u52a0\u8f7dSpaCy\u7684\u6a21\u578b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">nlp = spacy.load(&#39;en_core_web_sm&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u53bb\u9664\u505c\u7528\u8bcd<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528SpaCy\u5e93\u63d0\u4f9b\u7684\u505c\u7528\u8bcd\u5217\u8868\uff0c\u7ed3\u5408\u6a21\u578b\u5bf9\u6587\u672c\u8fdb\u884c\u5904\u7406\uff0c\u5e76\u53bb\u9664\u505c\u7528\u8bcd\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">text = &quot;This is a sample sentence, showing off the stop words filtration.&quot;<\/p>\n<p>doc = nlp(text)<\/p>\n<p>filtered_sentence = [token.text for token in doc if not token.is_stop]<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528gensim\u5e93\u53bb\u9664\u505c\u7528\u8bcd<\/h3>\n<\/p>\n<p><p>gensim\u662f\u53e6\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5\u548c\u5bfc\u5165gensim\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u4f7f\u7528gensim\u5e93\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u5148\u5b89\u88c5gensim\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install gensim<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165gensim\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from gensim.parsing.preprocessing import remove_stopwords<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u53bb\u9664\u505c\u7528\u8bcd<\/h4>\n<\/p>\n<p><p>gensim\u5e93\u63d0\u4f9b\u4e86remove_stopwords\u51fd\u6570\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u8f7b\u677e\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">text = &quot;This is a sample sentence, showing off the stop words filtration.&quot;<\/p>\n<p>filtered_sentence = remove_stopwords(text)<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\u53bb\u9664\u505c\u7528\u8bcd<\/h3>\n<\/p>\n<p><p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u4f7f\u7528\u81ea\u5b9a\u4e49\u7684\u505c\u7528\u8bcd\u5217\u8868\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\u53bb\u9664\u505c\u7528\u8bcd\u7684\u793a\u4f8b\u4ee3\u7801\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u5b9a\u4e49\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b9a\u4e49\u4e00\u4e2a\u81ea\u5b9a\u4e49\u7684\u505c\u7528\u8bcd\u5217\u8868\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">custom_stop_words = {&quot;is&quot;, &quot;a&quot;, &quot;the&quot;}<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5206\u8bcd\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>\u4e0e\u4e4b\u524d\u7684\u65b9\u6cd5\u4e00\u6837\uff0c\u6211\u4eec\u9700\u8981\u5148\u5c06\u6587\u672c\u8fdb\u884c\u5206\u8bcd\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">text = &quot;This is a sample sentence, showing off the stop words filtration.&quot;<\/p>\n<p>word_tokens = word_tokenize(text)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u53bb\u9664\u505c\u7528\u8bcd<\/h4>\n<\/p>\n<p><p>\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5217\u8868\u63a8\u5bfc\u5f0f\u5c06\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\u53bb\u9664\uff0c\u5f97\u5230\u8fc7\u6ee4\u540e\u7684\u53e5\u5b50\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">filtered_sentence = [w for w in word_tokens if not w.lower() in custom_stop_words]<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u6bd4\u8f83\u4e0d\u540c\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9<\/h3>\n<\/p>\n<p><p>\u5728\u53bb\u9664\u505c\u7528\u8bcd\u65f6\uff0c\u4e0d\u540c\u7684\u65b9\u6cd5\u5404\u6709\u4f18\u7f3a\u70b9\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>1\u3001NLTK\u5e93\u7684\u4f18\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u529f\u80fd\u5f3a\u5927\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u3002<\/li>\n<li>\u793e\u533a\u6d3b\u8dc3\uff0c\u6709\u4e30\u5bcc\u7684\u6587\u6863\u548c\u793a\u4f8b\u4ee3\u7801\u3002<\/li>\n<\/ul>\n<p><p><strong>\u7f3a\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u9700\u8981\u624b\u52a8\u4e0b\u8f7d\u505c\u7528\u8bcd\u5217\u8868\u548c\u5206\u8bcd\u5668\u3002<\/li>\n<li>\u5904\u7406\u901f\u5ea6\u76f8\u5bf9\u8f83\u6162\u3002<\/li>\n<\/ul>\n<p><h4>2\u3001SpaCy\u5e93\u7684\u4f18\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u529f\u80fd\u5f3a\u5927\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u3002<\/li>\n<li>\u6a21\u578b\u52a0\u8f7d\u540e\uff0c\u5904\u7406\u901f\u5ea6\u5feb\u3002<\/li>\n<\/ul>\n<p><p><strong>\u7f3a\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u9700\u8981\u4e0b\u8f7d\u5b89\u88c5\u6a21\u578b\uff0c\u521d\u6b21\u4f7f\u7528\u65f6\u53ef\u80fd\u6bd4\u8f83\u9ebb\u70e6\u3002<\/li>\n<li>\u5bf9\u4e8e\u67d0\u4e9b\u9ad8\u7ea7\u529f\u80fd\uff0c\u53ef\u80fd\u9700\u8981\u8f83\u9ad8\u7684\u5b66\u4e60\u6210\u672c\u3002<\/li>\n<\/ul>\n<p><h4>3\u3001gensim\u5e93\u7684\u4f18\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u529f\u80fd\u5f3a\u5927\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u3002<\/li>\n<li>\u4f7f\u7528\u7b80\u5355\uff0c\u53bb\u9664\u505c\u7528\u8bcd\u7684\u4ee3\u7801\u8f83\u4e3a\u7b80\u6d01\u3002<\/li>\n<\/ul>\n<p><p><strong>\u7f3a\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u53bb\u9664\u505c\u7528\u8bcd\u7684\u529f\u80fd\u8f83\u4e3a\u5355\u4e00\uff0c\u53ef\u80fd\u9700\u8981\u7ed3\u5408\u5176\u4ed6\u5de5\u5177\u4f7f\u7528\u3002<\/li>\n<li>\u5904\u7406\u901f\u5ea6\u76f8\u5bf9\u8f83\u6162\u3002<\/li>\n<\/ul>\n<p><h4>4\u3001\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\u7684\u4f18\u7f3a\u70b9<\/h4>\n<\/p>\n<p><p><strong>\u4f18\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u7075\u6d3b\u6027\u9ad8\uff0c\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\u3002<\/li>\n<li>\u4ee3\u7801\u7b80\u5355\uff0c\u6613\u4e8e\u7406\u89e3\u548c\u4f7f\u7528\u3002<\/li>\n<\/ul>\n<p><p><strong>\u7f3a\u70b9\uff1a<\/strong><\/p>\n<\/p>\n<ul>\n<li>\u9700\u8981\u624b\u52a8\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\uff0c\u53ef\u80fd\u8f83\u4e3a\u7e41\u7410\u3002<\/li>\n<li>\u5bf9\u4e8e\u5927\u89c4\u6a21\u6587\u672c\u5904\u7406\uff0c\u6027\u80fd\u53ef\u80fd\u8f83\u5dee\u3002<\/li>\n<\/ul>\n<p><h3>\u516d\u3001\u5b9e\u6218\u6848\u4f8b\uff1a\u53bb\u9664\u505c\u7528\u8bcd\u540e\u7684\u6587\u672c\u5206\u6790<\/h3>\n<\/p>\n<p><p>\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u53bb\u9664\u505c\u7528\u8bcd\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6587\u672c\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5206\u6790\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u5b9e\u6218\u6848\u4f8b\uff0c\u5c55\u793a\u4e86\u5982\u4f55\u5728\u53bb\u9664\u505c\u7528\u8bcd\u540e\u5bf9\u6587\u672c\u8fdb\u884c\u5206\u6790\u3002<\/p>\n<\/p>\n<p><h4>1\u3001\u6570\u636e\u51c6\u5907<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u51c6\u5907\u4e00\u6bb5\u793a\u4f8b\u6587\u672c\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">text = &quot;&quot;&quot;<\/p>\n<p>Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. The ultimate goal of NLP is to enable computers to understand, interpret, and generate human language in a way that is both meaningful and useful. NLP techniques are used in various applications such as sentiment analysis, machine translation, chatbots, and information extraction.<\/p>\n<p>&quot;&quot;&quot;<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u53bb\u9664\u505c\u7528\u8bcd<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528NLTK\u5e93\u53bb\u9664\u6587\u672c\u4e2d\u7684\u505c\u7528\u8bcd\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import nltk<\/p>\n<p>from nltk.corpus import stopwords<\/p>\n<p>from nltk.tokenize import word_tokenize<\/p>\n<p>nltk.download(&#39;stopwords&#39;)<\/p>\n<p>nltk.download(&#39;punkt&#39;)<\/p>\n<p>stop_words = set(stopwords.words(&#39;english&#39;))<\/p>\n<p>word_tokens = word_tokenize(text)<\/p>\n<p>filtered_sentence = [w for w in word_tokens if not w.lower() in stop_words]<\/p>\n<p>print(filtered_sentence)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u8bcd\u9891\u7edf\u8ba1<\/h4>\n<\/p>\n<p><p>\u53bb\u9664\u505c\u7528\u8bcd\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6587\u672c\u4e2d\u7684\u8bcd\u8fdb\u884c\u7edf\u8ba1\uff0c\u5206\u6790\u5176\u8bcd\u9891\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from collections import Counter<\/p>\n<p>word_counts = Counter(filtered_sentence)<\/p>\n<p>print(word_counts)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u8bcd\u4e91\u5c55\u793a<\/h4>\n<\/p>\n<p><p>\u4e3a\u4e86\u66f4\u76f4\u89c2\u5730\u5c55\u793a\u6587\u672c\u4e2d\u7684\u5173\u952e\u8bcd\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u8bcd\u4e91\uff08Word Cloud\uff09\u8fdb\u884c\u53ef\u89c6\u5316\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5wordcloud\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install wordcloud<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u751f\u6210\u8bcd\u4e91\u5e76\u8fdb\u884c\u5c55\u793a\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from wordcloud import WordCloud<\/p>\n<p>import matplotlib.pyplot as plt<\/p>\n<p>wordcloud = WordCloud(width=800, height=400, background_color=&#39;white&#39;).generate_from_frequencies(word_counts)<\/p>\n<p>plt.figure(figsize=(10, 5))<\/p>\n<p>plt.imshow(wordcloud, interpolation=&#39;bilinear&#39;)<\/p>\n<p>plt.axis(&#39;off&#39;)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u672c\u6587\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u53bb\u9664Python\u4e2d\u7684\u505c\u7528\u8bcd\uff0c\u5e76\u63d0\u4f9b\u4e86\u56db\u79cd\u5e38\u7528\u7684\u65b9\u6cd5\uff1a<strong>\u4f7f\u7528NLTK\u5e93\u3001\u4f7f\u7528SpaCy\u5e93\u3001\u4f7f\u7528gensim\u5e93\u3001\u4f7f\u7528\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868<\/strong>\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u4f18\u7f3a\u70b9\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u3002\u5728\u53bb\u9664\u505c\u7528\u8bcd\u540e\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u5bf9\u6587\u672c\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5206\u6790\uff0c\u4f8b\u5982\u8bcd\u9891\u7edf\u8ba1\u548c\u8bcd\u4e91\u5c55\u793a\uff0c\u4ece\u800c\u66f4\u597d\u5730\u7406\u89e3\u548c\u5229\u7528\u6587\u672c\u6570\u636e\u3002<\/p>\n<\/p>\n<p><h3>\u516b\u3001\u53c2\u8003\u8d44\u6599<\/h3>\n<\/p>\n<ol>\n<li>NLTK\u5b98\u65b9\u6587\u6863\uff1a<a href=\"https:\/\/www.nltk.org\/\">https:\/\/www.nltk.org\/<\/a><\/li>\n<li>SpaCy\u5b98\u65b9\u6587\u6863\uff1a<a href=\"https:\/\/spacy.io\/\">https:\/\/spacy.io\/<\/a><\/li>\n<li>gensim\u5b98\u65b9\u6587\u6863\uff1a<a href=\"https:\/\/radimrehurek.com\/gensim\/\">https:\/\/radimrehurek.com\/gensim\/<\/a><\/li>\n<li>wordcloud\u5b98\u65b9\u6587\u6863\uff1a<a href=\"https:\/\/github.com\/amueller\/word_cloud\">https:\/\/github.com\/amueller\/word_cloud<\/a><\/li>\n<\/ol>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u5185\u5bb9\u7684\u5b66\u4e60\u548c\u5b9e\u8df5\uff0c\u6211\u4eec\u53ef\u4ee5\u638c\u63e1\u53bb\u9664\u505c\u7528\u8bcd\u7684\u591a\u79cd\u65b9\u6cd5\uff0c\u5e76\u5728\u5b9e\u9645\u9879\u76ee\u4e2d\u5e94\u7528\u8fd9\u4e9b\u65b9\u6cd5\u8fdb\u884c\u6587\u672c\u5206\u6790\u548c\u5904\u7406\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff01<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u8bc6\u522b\u505c\u7528\u8bcd\uff1f<\/strong><br \/>\u8bc6\u522b\u505c\u7528\u8bcd\u901a\u5e38\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u7b2c\u4e00\u6b65\u3002Python\u4e2d\u6709\u591a\u4e2a\u5e93\u53ef\u4ee5\u5e2e\u52a9\u8bc6\u522b\u548c\u5904\u7406\u505c\u7528\u8bcd\uff0c\u4f8b\u5982NLTK\u548cspaCy\u3002\u4f7f\u7528NLTK\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u4e0b\u8f7d\u505c\u7528\u8bcd\u5217\u8868\u5e76\u4f7f\u7528\u5b83\u4eec\u6765\u8fc7\u6ee4\u6587\u672c\u3002\u901a\u8fc7\u5c06\u6587\u672c\u5206\u8bcd\u5e76\u68c0\u67e5\u6bcf\u4e2a\u8bcd\u662f\u5426\u5728\u505c\u7528\u8bcd\u5217\u8868\u4e2d\uff0c\u53ef\u4ee5\u8f7b\u677e\u8bc6\u522b\u5e76\u53bb\u6389\u505c\u7528\u8bcd\u3002<\/p>\n<p><strong>\u4f7f\u7528Python\u53bb\u6389\u505c\u7528\u8bcd\u7684\u6700\u4f73\u5b9e\u8df5\u662f\u4ec0\u4e48\uff1f<\/strong><br \/>\u53bb\u6389\u505c\u7528\u8bcd\u7684\u6700\u4f73\u5b9e\u8df5\u5305\u62ec\u4f7f\u7528\u4e13\u4e1a\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\uff0c\u5982NLTK\u3001spaCy\u6216Gensim\u3002\u8fd9\u4e9b\u5e93\u63d0\u4f9b\u4e86\u73b0\u6210\u7684\u505c\u7528\u8bcd\u5217\u8868\u548c\u5de5\u5177\u6765\u5904\u7406\u6587\u672c\u6570\u636e\u3002\u6b64\u5916\uff0c\u7528\u6237\u53ef\u4ee5\u6839\u636e\u7279\u5b9a\u7684\u5e94\u7528\u573a\u666f\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5217\u8868\uff0c\u4ee5\u786e\u4fdd\u8fc7\u6ee4\u6389\u4e0d\u5fc5\u8981\u7684\u8bcd\u6c47\uff0c\u4ece\u800c\u63d0\u9ad8\u6587\u672c\u5206\u6790\u7684\u51c6\u786e\u6027\u3002<\/p>\n<p><strong>\u53bb\u6389\u505c\u7528\u8bcd\u540e\uff0c\u6587\u672c\u5206\u6790\u7684\u6548\u679c\u4f1a\u6709\u54ea\u4e9b\u6539\u53d8\uff1f<\/strong><br 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