{"id":476450,"date":"2023-08-09T07:29:55","date_gmt":"2023-08-09T07:29:55","guid":{"rendered":""},"modified":"2023-09-05T11:12:45","modified_gmt":"2023-09-05T11:12:45","slug":"cosine-similarity","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/kr\/wiki\/cosine-similarity\/","title":{"rendered":"\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131"},"content":{"rendered":"<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub0b4\ubd80 \uacf1 \uacf5\uac04\uc5d0\uc11c 0\uc774 \uc544\ub2cc \ub450 \ubca1\ud130 \uac04\uc758 \uc720\uc0ac\uc131\uc744 \uce21\uc815\ud558\ub294 \uc218\ud559\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP)\uc758 \uae30\ubcf8 \uac1c\ub150\uc785\ub2c8\ub2e4. \uc815\ubcf4 \uac80\uc0c9, \ud14d\uc2a4\ud2b8 \ub9c8\uc774\ub2dd, \ucd94\ucc9c \uc2dc\uc2a4\ud15c \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ub110\ub9ac \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc774 \uae30\uc0ac\uc5d0\uc11c\ub294 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \uc5ed\uc0ac, \ub0b4\ubd80 \uad6c\uc870, \uc720\ud615, \uc6a9\ub3c4 \ubc0f \ud5a5\ud6c4 \uc804\ub9dd\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc54c\uc544\ubd05\ub2c8\ub2e4.<\/p>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \uae30\uc6d0\uacfc \uadf8\uc5d0 \ub300\ud55c \uccab \ubc88\uc9f8 \uc5b8\uae09\uc758 \uc5ed\uc0ac<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131 \uac1c\ub150\uc740 \uc2a4\uc704\uc2a4 \uc218\ud559\uc790 Adrien-Marie Legendre\uac00 \ud0c0\uc6d0 \uc801\ubd84\uc5d0 \ub300\ud55c \uc5f0\uad6c\uc758 \uc77c\ubd80\ub85c \uc774 \uac1c\ub150\uc744 \ub3c4\uc785\ud588\ub358 19\uc138\uae30 \ucd08\ub85c \uac70\uc2ac\ub7ec \uc62c\ub77c\uac11\ub2c8\ub2e4. \uc774\ud6c4 20\uc138\uae30\uc5d0 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \uc815\ubcf4 \uac80\uc0c9 \ubd84\uc57c\uc640 NLP\uc5d0\uc11c \ubb38\uc11c\uc640 \ud14d\uc2a4\ud2b8 \uc720\uc0ac\uc131\uc744 \ube44\uad50\ud558\ub294 \uc720\uc6a9\ud55c \ucc99\ub3c4\ub85c \ud65c\uc6a9\ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \uc815\ubcf4\uc785\ub2c8\ub2e4. \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131 \uc8fc\uc81c \ud655\uc7a5<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\ucc28\uc6d0 \uacf5\uac04\uc5d0\uc11c \ube44\uad50\ub418\ub294 \ubb38\uc11c\ub098 \ud14d\uc2a4\ud2b8\ub97c \ub098\ud0c0\ub0b4\ub294 \ub450 \ubca1\ud130 \uc0ac\uc774\uc758 \uac01\ub3c4\uc758 \ucf54\uc0ac\uc778\uc744 \uacc4\uc0b0\ud569\ub2c8\ub2e4. \ub450 \ubca1\ud130 A\uc640 B \uc0ac\uc774\uc758 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \uacf5\uc2dd\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><div class=\"bg-black rounded-md mb-4\"><div class=\"flex items-center relative text-gray-200 bg-gray-800 px-4 py-2 text-xs font-sans justify-between rounded-t-md\"><span>CSS<\/span><button class=\"flex ml-auto gap-2\"><svg stroke=\"currentColor\" fill=\"none\" stroke-width=\"2\" viewbox=\"0 0 24 24\" stroke-linecap=\"round\" stroke-linejoin=\"round\" class=\"h-4 w-4\" height=\"1em\" width=\"1em\" ><path d=\"M16 4h2a2 2 0 0 1 2 2v14a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2V6a2 2 0 0 1 2-2h2\"><\/path><rect x=\"8\" y=\"2\" width=\"8\" height=\"4\" rx=\"1\" ry=\"1\"><\/rect><\/svg>\ucf54\ub4dc \ubcf5\uc0ac<\/button><\/div><div class=\"p-4 overflow-y-auto\"><code class=\"!whitespace-pre hljs language-css\" data-no-translation=\"\">Cosine Similarity(<span class=\"hljs-selector-tag\">A<\/span>, <span class=\"hljs-selector-tag\">B<\/span>) = (<span class=\"hljs-selector-tag\">A<\/span> \u00b7 <span class=\"hljs-selector-tag\">B<\/span>) \/ (||<span class=\"hljs-selector-tag\">A<\/span>|| * ||<span class=\"hljs-selector-tag\">B<\/span>||)\n<\/code><\/div><\/div><\/pre>\n<p>\uc5b4\ub514 <code data-no-translation=\"\">(A \u00b7 B)<\/code> \ub294 \ubca1\ud130 A\uc640 B\uc758 \ub0b4\uc801\uc744 \ub098\ud0c0\ub0b4\uace0, <code data-no-translation=\"\">||A||<\/code> \uadf8\ub9ac\uace0 <code data-no-translation=\"\">||B||<\/code> \ub294 \uac01\uac01 \ubca1\ud130 A\uc640 B\uc758 \ud06c\uae30(\ub610\ub294 \ub178\ub984)\uc785\ub2c8\ub2e4.<\/p>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \ubc94\uc704\ub294 -1\uc5d0\uc11c 1\uae4c\uc9c0\uc774\uba70, -1\uc740 \uc644\uc804\ud55c \ube44\uc720\uc0ac\uc131\uc744 \ub098\ud0c0\ub0b4\uace0, 1\uc740 \uc808\ub300 \uc720\uc0ac\uc131\uc744 \ub098\ud0c0\ub0b4\uace0, 0\uc740 \uc9c1\uad50\uc131(\uc720\uc0ac\uc131 \uc5c6\uc74c)\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/p>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \ub0b4\ubd80 \uad6c\uc870. \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc774 \uc791\ub3d9\ud558\ub294 \ubc29\uc2dd<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \uace0\ucc28\uc6d0 \uacf5\uac04\uc758 \uc218\uce58 \ud45c\ud604(\ubca1\ud130)\uc73c\ub85c \ubcc0\ud658\ud558\uc5ec \uc791\ub3d9\ud569\ub2c8\ub2e4. \uac01 \ucc28\uc6d0\uc740 \ub370\uc774\ud130\uc138\ud2b8\uc758 \uace0\uc720\ud55c \uc6a9\uc5b4\uc5d0 \ud574\ub2f9\ud569\ub2c8\ub2e4. \uadf8\ub7f0 \ub2e4\uc74c \ub450 \ubb38\uc11c \uac04\uc758 \uc720\uc0ac\uc131\uc740 \ud574\ub2f9 \ubca1\ud130 \uac04\uc758 \uac01\ub3c4\ub97c \uae30\ubc18\uc73c\ub85c \uacb0\uc815\ub429\ub2c8\ub2e4.<\/p>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \ud504\ub85c\uc138\uc2a4\uc5d0\ub294 \ub2e4\uc74c \ub2e8\uacc4\uac00 \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/p>\n<ol>\n<li>\ud14d\uc2a4\ud2b8 \uc804\ucc98\ub9ac: \ubd88\uc6a9 \ub2e8\uc5b4, \ud2b9\uc218 \ubb38\uc790\ub97c \uc81c\uac70\ud558\uace0 \ud615\ud0dc\uc18c \ubd84\uc11d \ub610\ub294 \uc6d0\ud615 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uc5ec \ud14d\uc2a4\ud2b8\ub97c \ud45c\uc900\ud654\ud569\ub2c8\ub2e4.<\/li>\n<li>\uc6a9\uc5b4 \ube48\ub3c4(TF) \uacc4\uc0b0: \ubb38\uc11c\uc5d0\uc11c \uac01 \uc6a9\uc5b4\uc758 \ube48\ub3c4\ub97c \uacc4\uc0b0\ud569\ub2c8\ub2e4.<\/li>\n<li>\uc5ed\ubb38\uc11c \ube48\ub3c4(IDF) \uacc4\uc0b0: \ubaa8\ub4e0 \ubb38\uc11c\uc5d0\uc11c \uac01 \uc6a9\uc5b4\uc758 \uc911\uc694\ub3c4\ub97c \uce21\uc815\ud558\uc5ec \ud76c\uadc0\ud55c \uc6a9\uc5b4\uc5d0 \ub354 \ub192\uc740 \uac00\uc911\uce58\ub97c \ubd80\uc5ec\ud569\ub2c8\ub2e4.<\/li>\n<li>TF-IDF \uacc4\uc0b0: TF\uc640 IDF\ub97c \uacb0\ud569\ud558\uc5ec \ubb38\uc11c\uc758 \ucd5c\uc885 \uc218\uce58 \ud45c\ud604\uc744 \uc5bb\uc2b5\ub2c8\ub2e4.<\/li>\n<li>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131 \uacc4\uc0b0: \ubb38\uc11c\uc758 TF-IDF \ubca1\ud130\ub97c \uc0ac\uc6a9\ud558\uc5ec \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \uc8fc\uc694 \ud2b9\uc9d5 \ubd84\uc11d<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ud14d\uc2a4\ud2b8 \ube44\uad50 \uc791\uc5c5\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\ub294 \uba87 \uac00\uc9c0 \uc8fc\uc694 \uae30\ub2a5\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n<ol>\n<li><strong>\uaddc\ubaa8 \ubd88\ubcc0<\/strong>: \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ubca1\ud130\uc758 \ud06c\uae30\uc5d0 \uc601\ud5a5\uc744 \ubc1b\uc9c0 \uc54a\uc73c\ubbc0\ub85c \ubb38\uc11c \uae38\uc774\uc758 \ubcc0\ud654\uc5d0 \uac15\uac74\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ub2a5\ub960<\/strong>: \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uacc4\uc0b0\ud558\ub294 \uac83\uc740 \ub300\uaddc\ubaa8 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc138\ud2b8\uc758 \uacbd\uc6b0\uc5d0\ub3c4 \uacc4\uc0b0\uc801\uc73c\ub85c \ud6a8\uc728\uc801\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\ud574\uc11d \uac00\ub2a5\uc131<\/strong>: \uc720\uc0ac\ub3c4 \uc810\uc218\ub294 -1\ubd80\ud130 1\uae4c\uc9c0\ub85c \uc9c1\uad00\uc801\uc778 \ud574\uc11d\uc744 \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ud14d\uc2a4\ud2b8 \uc758\ubbf8 \uc720\uc0ac\uc131<\/strong>: \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ud14d\uc2a4\ud2b8 \uac04\uc758 \uc758\ubbf8\uc801 \uc720\uc0ac\uc131\uc744 \uace0\ub824\ud558\uc5ec \ub0b4\uc6a9 \uae30\ubc18 \ucd94\ucc9c \ubc0f \ud074\ub7ec\uc2a4\ud130\ub9c1\uc5d0 \uc801\ud569\ud569\ub2c8\ub2e4.<\/li>\n<\/ol>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \uc720\ud615<\/h2>\n<p>\uc77c\ubc18\uc801\uc73c\ub85c \uc0ac\uc6a9\ub418\ub294 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc5d0\ub294 \ub450 \uac00\uc9c0 \uae30\ubcf8 \uc720\ud615\uc774 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ol>\n<li><strong>\uace0\uc804\uc801\uc778 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/strong>: \uc774\ub294 \ubb38\uc11c\uc758 TF-IDF \ud45c\ud604\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc55e\uc11c \ub17c\uc758\ud55c \ud45c\uc900 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\uc774\uc9c4 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/strong>: \uc774 \ubcc0\ud615\uc5d0\uc11c \ubca1\ud130\ub294 \uc774\uc9c4\uc218\uc774\uba70 \ubb38\uc11c\uc5d0 \uc6a9\uc5b4\uac00 \uc788\ub294\uc9c0(1) \ub610\ub294 \ubd80\uc7ac(0)\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/li>\n<\/ol>\n<p>\ub450 \uac00\uc9c0 \uc720\ud615\uc758 \ube44\uad50\ud45c\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<table>\n<thead>\n<tr>\n<th><\/th>\n<th>\uace0\uc804\uc801\uc778 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/th>\n<th>\uc774\uc9c4 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\ubca1\ud130 \ud45c\ud604<\/td>\n<td>TF-IDF<\/td>\n<td>\ubc14\uc774\ub108\ub9ac<\/td>\n<\/tr>\n<tr>\n<td>\ud574\uc11d \uac00\ub2a5\uc131<\/td>\n<td>\uc2e4\uc218 \uac12(-1~1)<\/td>\n<td>\ubc14\uc774\ub108\ub9ac(0 \ub610\ub294 1)<\/td>\n<\/tr>\n<tr>\n<td>\uc801\ud569<\/td>\n<td>\ud14d\uc2a4\ud2b8 \uae30\ubc18 \uc560\ud50c\ub9ac\ucf00\uc774\uc158<\/td>\n<td>\ud76c\uc18c \ub370\uc774\ud130 \uc2dc\ub098\ub9ac\uc624<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\ub3c4 \ud65c\uc6a9\ubc29\ubc95\uacfc \ud65c\uc6a9\uc5d0 \ub530\ub978 \ubb38\uc81c\uc810 \ubc0f \ud574\uacb0\ubc29\ubc95<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\uc591\ud55c \ub3c4\uba54\uc778\uc5d0\uc11c \uc751\uc6a9 \ud504\ub85c\uadf8\ub7a8\uc744 \ucc3e\uc2b5\ub2c8\ub2e4.<\/p>\n<ol>\n<li><strong>\uc815\ubcf4 \uac80\uc0c9<\/strong>: \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ucffc\ub9ac\uc640\uc758 \uad00\ub828\uc131\uc744 \uae30\uc900\uc73c\ub85c \ubb38\uc11c \uc21c\uc704\ub97c \uc9c0\uc815\ud558\uc5ec \ud6a8\uc728\uc801\uc778 \uac80\uc0c9 \uc5d4\uc9c4\uc744 \ud65c\uc131\ud654\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4.<\/li>\n<li><strong>\ubb38\uc11c \ud074\ub7ec\uc2a4\ud130\ub9c1<\/strong>: \ub354 \ub098\uc740 \uad6c\uc131 \ubc0f \ubd84\uc11d\uc744 \uc704\ud574 \uc720\uc0ac\ud55c \ubb38\uc11c\ub97c \uadf8\ub8f9\ud654\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4.<\/li>\n<li><strong>\ud611\uc5c5 \ud544\ud130\ub9c1<\/strong>: \ucd94\ucc9c \uc2dc\uc2a4\ud15c\uc740 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uc774\uc6a9\ud558\uc5ec \ube44\uc2b7\ud55c \ucde8\ud5a5\uc744 \uac00\uc9c4 \uc0ac\uc6a9\uc790\uc5d0\uac8c \uc0c1\ud488\uc744 \ucd94\ucc9c\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ud45c\uc808 \ud0d0\uc9c0<\/strong>: \uc11c\ub85c \ub2e4\ub978 \ubb38\uc11c\uc5d0\uc11c \uc720\uc0ac\ud55c \ud14d\uc2a4\ud2b8 \uc138\uadf8\uba3c\ud2b8\ub97c \uc2dd\ubcc4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ol>\n<p>\uadf8\ub7ec\ub098 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \uacbd\uc6b0\uc5d0 \ubb38\uc81c\uc5d0 \uc9c1\uba74\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\ud76c\uc18c\uc131<\/strong>: \uace0\ucc28\uc6d0 \ud76c\uc18c \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud560 \ub54c \uc720\uc0ac\uc131 \uc810\uc218\ub294 \uadf8\ub2e4\uc9c0 \uc720\uc775\ud558\uc9c0 \uc54a\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\uc5b8\uc5b4 \uc758\uc874\uc131<\/strong>: \ubb38\ubc95\uc774\ub098 \ub2e8\uc5b4 \uc21c\uc11c\uac00 \ubcf5\uc7a1\ud55c \uc5b8\uc5b4\uc5d0\uc11c\ub294 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc774 \ubb38\ub9e5\uc744 \ud3ec\ucc29\ud558\uc9c0 \ubabb\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<p>\uc774\ub7ec\ud55c \ubb38\uc81c\ub97c \uadf9\ubcf5\ud558\uae30 \uc704\ud574 \ucc28\uc6d0 \ucd95\uc18c(\uc608: Singular Value Decomposition \uc0ac\uc6a9) \ubc0f \ub2e8\uc5b4 \uc784\ubca0\ub529(\uc608: Word2Vec)\uacfc \uac19\uc740 \uae30\uc220\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc131\ub2a5\uc744 \ud5a5\uc0c1\ud569\ub2c8\ub2e4.<\/p>\n<h2>\uc8fc\uc694 \ud2b9\uc9d5 \ubc0f \uae30\ud0c0 \uc720\uc0ac \uc6a9\uc5b4\uc640\uc758 \ube44\uad50<\/h2>\n<table>\n<thead>\n<tr>\n<th><\/th>\n<th>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/th>\n<th>\uc790\uce74\ub4dc \uc720\uc0ac\uc131<\/th>\n<th>\uc720\ud074\ub9ac\ub4dc \uac70\ub9ac<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\uce21\uc815 \uc720\ud615<\/td>\n<td>\uc720\uc0ac\uc131<\/td>\n<td>\uc720\uc0ac\uc131<\/td>\n<td>\ucc28\uc774\uc810<\/td>\n<\/tr>\n<tr>\n<td>\ubc94\uc704<\/td>\n<td>-1 \ub300 1<\/td>\n<td>0 \ub300 1<\/td>\n<td>0~\ubb34\ud55c<\/td>\n<\/tr>\n<tr>\n<td>\uc801\uc6a9 \uac00\ub2a5\uc131<\/td>\n<td>\ud14d\uc2a4\ud2b8 \ube44\uad50<\/td>\n<td>\ube44\uad50 \uc124\uc815<\/td>\n<td>\uc218\uce58\ud615 \ubca1\ud130<\/td>\n<\/tr>\n<tr>\n<td>\ucc28\uc6d0\uc131<\/td>\n<td>\uace0\ucc28\uc6d0<\/td>\n<td>\uc800\ucc28\uc6d0<\/td>\n<td>\uace0\ucc28\uc6d0<\/td>\n<\/tr>\n<tr>\n<td>\uacc4\uc0b0<\/td>\n<td>\ud6a8\uc728\uc801\uc778<\/td>\n<td>\ud6a8\uc728\uc801\uc778<\/td>\n<td>\uacc4\uc0b0 \uc9d1\uc57d\uc801<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc5d0 \uad00\ud55c \ubbf8\ub798\uc758 \uad00\uc810\uacfc \uae30\uc220<\/h2>\n<p>\uae30\uc220\uc774 \uacc4\uc18d \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \uadc0\uc911\ud55c \ub3c4\uad6c\ub85c \ub0a8\uc744 \uac83\uc73c\ub85c \uc608\uc0c1\ub429\ub2c8\ub2e4. \ub354\uc6b1 \uac15\ub825\ud55c \ud558\ub4dc\uc6e8\uc5b4\uc640 \uc54c\uace0\ub9ac\uc998\uc758 \ucd9c\ud604\uc73c\ub85c \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \uc138\ud2b8\ub97c \ucc98\ub9ac\ud558\uace0 \uc815\ud655\ud55c \uad8c\uc7a5 \uc0ac\ud56d\uc744 \uc81c\uacf5\ud558\ub294 \ub370 \ub354\uc6b1 \ud6a8\uc728\uc801\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4. \ub610\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubc0f \ub525 \ub7ec\ub2dd\uc5d0 \ub300\ud55c \uc9c0\uc18d\uc801\uc778 \uc5f0\uad6c\ub97c \ud1b5\ud574 \ud14d\uc2a4\ud2b8 \ud45c\ud604\uc774 \ud5a5\uc0c1\ub418\uc5b4 \uc720\uc0ac\uc131 \uacc4\uc0b0\uc758 \uc815\ud655\uc131\uc774 \ub354\uc6b1 \ud5a5\uc0c1\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\ud504\ub85d\uc2dc \uc11c\ubc84\ub97c \uc0ac\uc6a9\ud558\uac70\ub098 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uacfc \uc5f0\uacb0\ud558\ub294 \ubc29\ubc95<\/h2>\n<p>OneProxy\uc5d0\uc11c \uc81c\uacf5\ud558\ub294 \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \uc775\uba85\uc758 \uc548\uc804\ud55c \uc778\ud130\ub137 \uc561\uc138\uc2a4\ub97c \ucd09\uc9c4\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \uc9c1\uc811 \ud65c\uc6a9\ud558\uc9c0\ub294 \uc54a\uc9c0\ub9cc \ud14d\uc2a4\ud2b8 \ube44\uad50 \ub610\ub294 \ucf58\ud150\uce20 \uae30\ubc18 \ud544\ud130\ub9c1\uc744 \uc0ac\uc6a9\ud558\ub294 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ud3ec\ud568\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc744 \ud65c\uc6a9\ud558\uc5ec \uc0ac\uc6a9\uc790 \uc120\ud638\ub3c4\ub97c \ube44\uad50\ud558\uace0 \uad00\ub828 \ucf58\ud150\uce20\ub97c \uc81c\uc548\ud568\uc73c\ub85c\uc368 \ucd94\ucc9c \uc2dc\uc2a4\ud15c\uc758 \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c \uc0ac\uc6a9\uc790 \ucffc\ub9ac\uc640 \uc0c9\uc778\ud654\ub41c \ubb38\uc11c \uac04\uc758 \uc720\uc0ac\uc131 \uc810\uc218\ub97c \uae30\ubc18\uc73c\ub85c \uac80\uc0c9 \uacb0\uacfc\ub97c \ucd5c\uc801\ud654\ud558\uc5ec \uc815\ubcf4 \uac80\uc0c9 \uc791\uc5c5\uc744 \uc9c0\uc6d0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\uad00\ub828\ub41c \ub9c1\ud06c\ub4e4<\/h2>\n<p>\ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \ub2e4\uc74c \ub9ac\uc18c\uc2a4\ub97c \ucc38\uc870\ud558\uc138\uc694.<\/p>\n<ol>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Cosine_similarity\" target=\"_new\" rel=\"noopener nofollow\">Wikipedia \u2013 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.metrics.pairwise.cosine_similarity.html\" target=\"_new\" rel=\"noopener nofollow\">Scikit-learn \u2013 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131<\/a><\/li>\n<li><a href=\"https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.feature_extraction.text.TfidfVectorizer.html\" target=\"_new\" rel=\"noopener nofollow\">TfidfVectorizer \u2013 Sklearn \ubb38\uc11c<\/a><\/li>\n<li><a href=\"https:\/\/nlp.stanford.edu\/IR-book\/\" target=\"_new\" rel=\"noopener nofollow\">\uc815\ubcf4 \uac80\uc0c9 \uc18c\uac1c - Manning, Raghavan, Sch\u00fctze<\/a><\/li>\n<\/ol>\n<p>\uacb0\ub860\uc801\uc73c\ub85c, \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc740 NLP, \uc815\ubcf4 \uac80\uc0c9 \ubc0f \ucd94\ucc9c \uc2dc\uc2a4\ud15c\uc5d0 \uad11\ubc94\uc704\ud558\uac8c \uc801\uc6a9\ub418\ub294 \uac15\ub825\ud55c \uc218\ud559\uc801 \uac1c\ub150\uc785\ub2c8\ub2e4. \ub2e8\uc21c\uc131, \ud6a8\uc728\uc131 \ubc0f \ud574\uc11d \uac00\ub2a5\uc131\uc73c\ub85c \uc778\ud574 \ub2e4\uc591\ud55c \ud14d\uc2a4\ud2b8 \uae30\ubc18 \uc791\uc5c5\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\uba70, \uc9c0\uc18d\uc801\uc778 \uae30\uc220 \ubc1c\uc804\uc73c\ub85c \uc778\ud574 \ud5a5\ud6c4 \uae30\ub2a5\uc774 \ub354\uc6b1 \ud5a5\uc0c1\ub420 \uac83\uc73c\ub85c \uc608\uc0c1\ub429\ub2c8\ub2e4. \uae30\uc5c5\uacfc \uc5f0\uad6c\uc6d0\uc774 \ucf54\uc0ac\uc778 \uc720\uc0ac\uc131\uc758 \uc7a0\uc7ac\ub825\uc744 \uacc4\uc18d \ud65c\uc6a9\ud568\uc5d0 \ub530\ub77c OneProxy\uc640 \uac19\uc740 \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \uc548\uc804\ud558\uace0 \uc775\uba85\uc758 \uc778\ud130\ub137 \uc561\uc138\uc2a4\ub97c \ubcf4\uc7a5\ud558\uba74\uc11c \uc774\ub7ec\ud55c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc9c0\uc6d0\ud558\ub294 \ub370 \uc911\uc694\ud55c \uc5ed\ud560\uc744 \ud560 \uac83\uc785\ub2c8\ub2e4.<\/p>","protected":false},"featured_media":468030,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476450","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Cosine Similarity: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is Cosine similarity?","answer":"<p>Cosine similarity is a mathematical concept used to measure the similarity between two vectors in a multi-dimensional space. It is commonly applied in text analysis, recommendation systems, and information retrieval tasks.<\/p>"},{"question":"How does Cosine similarity work?","answer":"<p>Cosine similarity calculates the cosine of the angle between two vectors, representing the documents being compared. It ranges from -1 to 1, where -1 indicates complete dissimilarity, 1 indicates absolute similarity, and 0 indicates orthogonality (no similarity).<\/p>"},{"question":"What are the key features of Cosine similarity?","answer":"<p>Cosine similarity offers scale invariance, efficiency, interpretability, and the ability to measure textual semantic similarity.<\/p>"},{"question":"What types of Cosine similarity exist?","answer":"<p>There are two primary types: Classic Cosine Similarity, which uses TF-IDF representation, and Binary Cosine Similarity, which utilizes binary vectors.<\/p>"},{"question":"How can Cosine similarity be used?","answer":"<p>Cosine similarity finds applications in various fields, including information retrieval, document clustering, collaborative filtering, and plagiarism detection.<\/p>"},{"question":"What challenges does Cosine similarity face?","answer":"<p>Cosine similarity may encounter issues with sparsity and language dependence in certain scenarios. Techniques like dimensionality reduction and word embeddings can address these challenges.<\/p>"},{"question":"How does Cosine similarity compare to other similarity measures?","answer":"<p>Cosine similarity is distinct from Jaccard similarity and Euclidean distance in terms of range, applicability, dimensionality, and computation.<\/p>"},{"question":"What are the future perspectives of Cosine similarity?","answer":"<p>As technology advances, Cosine similarity is expected to remain a valuable tool with enhanced efficiency and accuracy in similarity calculations.<\/p>"},{"question":"How are proxy servers associated with Cosine similarity?","answer":"<p>While proxy servers like OneProxy don't directly utilize Cosine similarity, they can support applications that involve text comparison and content-based filtering, such as recommendation systems and information retrieval tasks. They also ensure secure internet access during these operations.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki\/476450","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki\/476450\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/media\/468030"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/media?parent=476450"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}