{"id":97890,"date":"2020-10-22T20:43:19","date_gmt":"2020-10-22T18:43:19","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/razbiraemsya-v-chem-raznicza-mezhdu-data-mining-i-data-extraction"},"modified":"2021-02-01T11:42:45","modified_gmt":"2021-02-01T09:42:45","slug":"razbiraemsya-v-chem-raznicza-mezhdu-data-mining-i-data-extraction","status":"publish","type":"post","link":"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/razbiraemsya-v-chem-raznicza-mezhdu-data-mining-i-data-extraction","title":{"rendered":"Zjist\u00edme, jak\u00fd je rozd\u00edl mezi Data Mining a Data Extraction","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/524336\/\"><img decoding=\"async\" alt=\"Zjist\u00edme, jak\u00fd je rozd\u00edl mezi Data Mining a Data Extraction\" src=\"\/wp-content\/uploads\/2020\/10\/bd0e140b564b7f6696b346865a91784f.png\" style=\"display:block;margin: 0 auto;\"><\/a><\/noindex><br \/>\nTyto dv\u011b m\u00f3dn\u00ed slova, spojen\u00e1 s Data Science, m\u00e1tou mnoho lid\u00ed v rozpac\u00edch. Data Mining je \u010dasto myln\u011b ch\u00e1p\u00e1n jako extrakce a z\u00edsk\u00e1v\u00e1n\u00ed dat, ale ve skute\u010dnosti je to mnohem slo\u017eit\u011bj\u0161\u00ed. V tomto p\u0159\u00edsp\u011bvku si ujasn\u00edme rozd\u00edl mezi Data Mining a Data Extraction.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h2>Co je to Data Mining?<\/h2>\n<p>Data mining, tak\u00e9 naz\u00fdvan\u00fd <strong>objevov\u00e1n\u00ed znalost\u00ed v datab\u00e1z\u00edch (KDD)<\/strong>, je metoda \u010dasto pou\u017e\u00edvan\u00e1 k anal\u00fdze velk\u00fdch objem\u016f dat pomoc\u00ed statistick\u00fdch a matematick\u00fdch metod za \u00fa\u010delem hled\u00e1n\u00ed skryt\u00fdch vzorc\u016f nebo trend\u016f a t\u011b\u017een\u00ed z nich hodnoty.<\/p>\n<h2>Co lze d\u011blat s pomoc\u00ed Data Mining?<\/h2>\n<p>Automatizac\u00ed procesu, <noindex><a rel=\"nofollow\" href=\"https:\/\/www.octoparse.com\/blog\/7-web-mining-tools-around-the-web\">n\u00e1stroje data mining<\/a><\/noindex> mohou proch\u00e1zet datab\u00e1ze a efektivn\u011b odhalovat skryt\u00e9 vzorce. Pro podniky se data mining \u010dasto pou\u017e\u00edv\u00e1 k odhalov\u00e1n\u00ed vzorc\u016f a souvislost\u00ed v datech, co\u017e pom\u00e1h\u00e1 p\u0159i optim\u00e1ln\u00edm rozhodov\u00e1n\u00ed v oblasti podnik\u00e1n\u00ed.<\/p>\n<h2>P\u0159\u00edklady pou\u017eit\u00ed<\/h2>\n<p>Pot\u00e9, co se na p\u0159elomu 90. let data mining roz\u0161\u00ed\u0159il, za\u010daly spole\u010dnosti v \u0161irok\u00e9 \u0161k\u00e1le odv\u011btv\u00ed, v\u010detn\u011b maloobchodu, financ\u00ed, zdravotnictv\u00ed, dopravy, telekomunikac\u00ed, elektronick\u00e9ho obchodov\u00e1n\u00ed atd., pou\u017e\u00edvat metody data mining pro z\u00edsk\u00e1v\u00e1n\u00ed informac\u00ed na z\u00e1klad\u011b dat. Data mining m\u016f\u017ee pomoci segmentovat z\u00e1kazn\u00edky, odhalit podvody, predikovat prodeje a mnohem v\u00edce.<\/p>\n<ul>\n<li><b>Segmentace z\u00e1kazn\u00edk\u016f<\/b><br \/>\nD\u00edky anal\u00fdze dat o z\u00e1kazn\u00edc\u00edch a identifikaci rys\u016f c\u00edlov\u00fdch z\u00e1kazn\u00edk\u016f mohou spole\u010dnosti vytv\u00e1\u0159et jejich specifick\u00e9 skupiny a nab\u00edzet jim speci\u00e1ln\u00ed nab\u00eddky odpov\u00eddaj\u00edc\u00ed jejich pot\u0159eb\u00e1m.<\/li>\n<li><b>Anal\u00fdza tr\u017en\u00edho ko\u0161\u00edku<\/b><br \/>\nTato metodika je zalo\u017eena na teorii, \u017ee pokud nakupujete ur\u010ditou skupinu zbo\u017e\u00ed, pravd\u011bpodobn\u011b si tak\u00e9 koup\u00edte jinou skupinu zbo\u017e\u00ed. Jeden zn\u00e1m\u00fd p\u0159\u00edklad: kdy\u017e otcov\u00e9 kupuj\u00ed plenky pro sv\u00e9 d\u011bti, obvykle kupuj\u00ed pivo spole\u010dn\u011b s plenami.<\/li>\n<li><b>Predikce prodeje<\/b><br \/>\nM\u016f\u017ee to vypadat podobn\u011b jako anal\u00fdza tr\u017en\u00edho ko\u0161\u00edku, ale tentokr\u00e1t se anal\u00fdza dat pou\u017e\u00edv\u00e1 k predikci, kdy z\u00e1kazn\u00edk znovu zakoup\u00ed produkt v budoucnu. Nap\u0159\u00edklad tren\u00e9r kupuje plechovku proteinu, kter\u00e1 by m\u011bla vydr\u017eet 9 m\u011bs\u00edc\u016f. Obchod, kter\u00fd prod\u00e1v\u00e1 tento protein, pl\u00e1nuje uv\u00e9st nov\u00fd za 9 m\u011bs\u00edc\u016f, aby tren\u00e9r znovu nakoupil.<\/li>\n<li><b>Odhalen\u00ed podvod\u016f<\/b><br \/>\nData mining pom\u00e1h\u00e1 p\u0159i vytv\u00e1\u0159en\u00ed model\u016f pro odhalen\u00ed podvod\u016f. Shroma\u017e\u010fov\u00e1n\u00edm vzork\u016f podvodn\u00fdch a pravdiv\u00fdch zpr\u00e1v z\u00edsk\u00e1vaj\u00ed podniky pr\u00e1vo ur\u010dit, kter\u00e9 operace jsou podez\u0159el\u00e9.<\/li>\n<li><b>Odhalen\u00ed vzor\u016f ve v\u00fdrob\u011b<\/b><br \/>\nV zpracovatelsk\u00e9m pr\u016fmyslu se data mining pou\u017e\u00edv\u00e1 k pomoci p\u0159i n\u00e1vrhu syst\u00e9m\u016f, identifikac\u00ed vztah\u016f mezi architekturou produktu, profilem a pot\u0159ebami z\u00e1kazn\u00edk\u016f. Data mining tak\u00e9 m\u016f\u017ee p\u0159edpov\u011bd\u011bt \u010dasov\u00e9 r\u00e1mce v\u00fdvoje produktu a n\u00e1klady.<\/li>\n<\/ul>\n<p>A to jsou jen n\u011bkter\u00e9 sc\u00e9n\u00e1\u0159e pou\u017eit\u00ed data miningu.<\/p>\n<h2>Etapy Data Miningu<\/h2>\n<p>Data mining je komplexn\u00ed proces sb\u011bru, v\u00fdb\u011bru, \u010di\u0161t\u011bn\u00ed, transformace a extrakce dat pro hodnocen\u00ed vzorc\u016f a nakonec pro z\u00edsk\u00e1n\u00ed hodnoty.<\/p>\n<p><img decoding=\"async\" alt=\"Zjist\u00edme, jak\u00fd je rozd\u00edl mezi Data Mining a Data Extraction\" src=\"\/wp-content\/uploads\/2020\/10\/0f601a9f32e2b9517f1a7deb0e353b5a.png\" style=\"display:block;margin: 0 auto;\"><\/p>\n<p>Obvykle lze cel\u00fd proces data miningu shrnout do 7 etap:<\/p>\n<ol>\n<li><b>\u010ci\u0161t\u011bn\u00ed dat<\/b><br \/>\nVe skute\u010dn\u00e9m sv\u011bt\u011b nejsou data v\u017edy \u010di\u0161t\u011bna a strukturov\u00e1na. \u010casto jsou hlu\u010dn\u00e1, ne\u00fapln\u00e1 a mohou obsahovat chyby. Aby se zajistilo, \u017ee v\u00fdsledek data miningu je p\u0159esn\u00fd, je t\u0159eba nejprve data vy\u010distit. N\u011bkter\u00e9 metody \u010di\u0161t\u011bn\u00ed zahrnuj\u00ed vypln\u011bn\u00ed chyb\u011bj\u00edc\u00edch hodnot, automatickou a ru\u010dn\u00ed kontrolu atd.<\/li>\n<li><b>Integrace dat<\/b><br \/>\nToto je etapa, kdy jsou data z r\u016fzn\u00fdch zdroj\u016f extrahov\u00e1na, kombinov\u00e1na a integrov\u00e1na. Zdroji mohou b\u00fdt datab\u00e1ze, textov\u00e9 soubory, tabulky, dokumenty, v\u00edcerozm\u011brn\u00e9 datov\u00e9 matice, internet a tak d\u00e1le.<\/li>\n<li><b>V\u00fdb\u011br dat<\/b><br \/>\nObvykle nejsou v\u0161echna integrovan\u00e1 data pot\u0159ebn\u00e1 pro data mining. V\u00fdb\u011br dat je etapa, kdy jsou z velk\u00e9 datab\u00e1ze vyb\u00edr\u00e1na a extrahov\u00e1na pouze u\u017eite\u010dn\u00e1 data.<\/li>\n<li><b>Transformace dat.<\/b><br \/>\nPo vybr\u00e1n\u00ed dat jsou transformov\u00e1na do forem vhodn\u00fdch pro t\u011b\u017ebu. Tento proces zahrnuje normalizaci, agregaci, generalizaci atd.<\/li>\n<li><b>Inteligentn\u00ed anal\u00fdza dat<\/b><br \/>\nZde p\u0159ich\u00e1z\u00ed nejd\u016fle\u017eit\u011bj\u0161\u00ed \u010d\u00e1st data miningu - vyu\u017eit\u00ed inteligentn\u00edch metod pro hled\u00e1n\u00ed vzorc\u016f v nich. Proces zahrnuje regresi, klasifikaci, predikci, shlukov\u00e1n\u00ed, studium asociac\u00ed a mnoho dal\u0161\u00edho.<\/li>\n<li><b>Hodnocen\u00ed modelu<\/b><br \/>\nTato etapa je zam\u011b\u0159ena na identifikaci potenci\u00e1ln\u011b u\u017eite\u010dn\u00fdch, snadno pochopiteln\u00fdch vzorc\u016f, stejn\u011b jako vzorc\u016f potvrzuj\u00edc\u00edch hypot\u00e9zy.<\/li>\n<li><b>Prezentace znalost\u00ed<\/b><br \/>\nNa z\u00e1v\u011bre\u010dn\u00e9m stupni je z\u00edskan\u00e1 informace prezentov\u00e1na atraktivn\u00edm zp\u016fsobem pomoc\u00ed metod pro prezentaci znalost\u00ed a vizualizaci.<\/li>\n<\/ol>\n<h2>Nev\u00fdhody Data Miningu<\/h2>\n<ul>\n<li><b>Velk\u00e9 investice \u010dasu a \u00fasil\u00ed<\/b><br \/>\nJeliko\u017e je t\u011b\u017eba dat dlouh\u00fdm a slo\u017eit\u00fdm procesem, vy\u017eaduje zna\u010dn\u00e9 pracovn\u00ed \u00fasil\u00ed kvalifikovan\u00fdch lid\u00ed. Odborn\u00edci na anal\u00fdzu dat mohou vyu\u017e\u00edvat v\u00fdkonn\u00e9 n\u00e1stroje na t\u011b\u017ebu dat, nicm\u00e9n\u011b pot\u0159ebuj\u00ed odborn\u00edky k p\u0159\u00edprav\u011b dat a pochopen\u00ed v\u00fdsledk\u016f. V d\u016fsledku toho m\u016f\u017ee zpracov\u00e1n\u00ed v\u0161ech informac\u00ed zabrat n\u011bjak\u00fd \u010das.<\/li>\n<li><b>Ochrana soukrom\u00ed a bezpe\u010dnost dat<\/b><br \/>\nJeliko\u017e data mining shroma\u017e\u010fuje informace o klientech pomoc\u00ed marketingov\u00fdch metod, m\u016f\u017ee to naru\u0161it soukrom\u00ed u\u017eivatel\u016f. Nav\u00edc se mohou hacke\u0159i dostat k dat\u016fm ulo\u017een\u00fdm v syst\u00e9mech pro t\u011b\u017ebu dat. To p\u0159edstavuje hrozbu pro bezpe\u010dnost dat klient\u016f. Pokud jsou odcizen\u00e1 data pou\u017eita nevhodn\u011b, m\u016f\u017ee to snadno po\u0161kodit ostatn\u00ed.<\/li>\n<\/ul>\n<blockquote><p>V\u00fd\u0161e uveden\u00e9 je stru\u010dn\u00e9 \u00favodn\u00ed sezn\u00e1men\u00ed s data miningem. Jak jsem ji\u017e zm\u00ednila, data mining zahrnuje proces shroma\u017e\u010fov\u00e1n\u00ed a integrace dat, kter\u00fd zahrnuje proces extrakce dat (data extraction). V tomto p\u0159\u00edpad\u011b lze s jistotou \u0159\u00edci, \u017ee extrakce dat m\u016f\u017ee b\u00fdt sou\u010d\u00e1st\u00ed dlouh\u00e9ho procesu data miningu.<\/p><\/blockquote>\n<h2>Co je to Data Extraction?<\/h2>\n<p>Tak\u00e9 zn\u00e1m\u00fd jako \u201eextrakce webov\u00fdch dat\u201c a \u201eweb scraping\u201c, tento proces p\u0159edstavuje akt extrakce dat z (obvykle nestrukturovan\u00fdch nebo \u0161patn\u011b strukturovan\u00fdch) zdroj\u016f dat do centralizovan\u00fdch m\u00edst a centralizaci na jednom m\u00edst\u011b pro uchov\u00e1n\u00ed nebo dal\u0161\u00ed zpracov\u00e1n\u00ed. Mezi nestrukturovan\u00e9 zdroje dat pat\u0159\u00ed webov\u00e9 str\u00e1nky, e-maily, dokumenty, soubory PDF, naskenovan\u00fd text, zpr\u00e1vy z mainframe, p\u00e1skov\u00e9 soubory, inzer\u00e1ty atd. Centralizovan\u00e9 \u00falo\u017ei\u0161t\u011b mohou b\u00fdt m\u00edstn\u00ed, cloudov\u00e1 nebo hybridn\u00ed. Je d\u016fle\u017eit\u00e9 m\u00edt na pam\u011bti, \u017ee extrakce dat neobsahuje zpracov\u00e1n\u00ed nebo dal\u0161\u00ed anal\u00fdzu, kter\u00e1 m\u016f\u017ee nastat pozd\u011bji.<\/p>\n<h2>Co lze d\u011blat s pomoc\u00ed Data Extraction?<\/h2>\n<p>Hlavn\u00ed c\u00edle extrakce dat se d\u011bl\u00ed do 3 kategori\u00ed.<\/p>\n<ul>\n<li><b>Archivace<\/b><br \/>\nExtrakce dat m\u016f\u017ee p\u0159ev\u00e9st data z fyzick\u00fdch form\u00e1t\u016f, jako jsou knihy, noviny a faktury, na digit\u00e1ln\u00ed form\u00e1ty, nap\u0159\u00edklad datab\u00e1ze pro ukl\u00e1d\u00e1n\u00ed nebo z\u00e1lohov\u00e1n\u00ed.<\/li>\n<li><b>Zm\u011bna form\u00e1tu dat<\/b><br \/>\nKdy\u017e chcete p\u0159en\u00e9st data ze sv\u00e9ho sou\u010dasn\u00e9ho webu na nov\u00fd, kter\u00fd je ve v\u00fdvoji, m\u016f\u017eete shrom\u00e1\u017edit data ze sv\u00e9ho vlastn\u00edho webu jejich extrakc\u00ed.<\/li>\n<li><b>Anal\u00fdza dat<\/b><br \/>\nDopl\u0148kov\u00e1 anal\u00fdza extrahovan\u00fdch dat je b\u011b\u017en\u00e1, aby se z\u00edskal p\u0159ehled o nich. M\u016f\u017ee to vypadat podobn\u011b jako anal\u00fdza dat p\u0159i data miningu, ale m\u011bjte na pam\u011bti, \u017ee anal\u00fdza dat je c\u00edlem jejich extrakce, nikoli jej\u00ed sou\u010d\u00e1st\u00ed. Krom\u011b toho se data analyzuj\u00ed jinak. P\u0159\u00edkladem jsou majitel\u00e9 internetov\u00fdch obchod\u016f, kte\u0159\u00ed extrahuj\u00ed informace o produktech z web\u016f elektronick\u00e9ho obchodov\u00e1n\u00ed, jako je Amazon, aby v re\u00e1ln\u00e9m \u010dase sledovali konkuren\u010dn\u00ed strategie. Stejn\u011b jako data mining, i extrakce dat je automatizovan\u00fd proces, kter\u00fd m\u00e1 mnoho v\u00fdhod. D\u0159\u00edve lid\u00e9 kop\u00edrovali a vkl\u00e1dali data ru\u010dn\u011b z jednoho m\u00edsta na druh\u00e9, co\u017e zab\u00edralo hodn\u011b \u010dasu. Extrakce dat urychluje shroma\u017e\u010fov\u00e1n\u00ed a v\u00fdrazn\u011b zvy\u0161uje p\u0159esnost extrahovan\u00fdch dat.<\/li>\n<\/ul>\n<h2>N\u011bkolik p\u0159\u00edklad\u016f pou\u017eit\u00ed extrakce dat<\/h2>\n<p>Podobn\u011b jako p\u0159i data miningu se extrakce dat \u0161iroce pou\u017e\u00edv\u00e1 v r\u016fzn\u00fdch odv\u011btv\u00edch pr\u016fmyslu. Krom\u011b sledov\u00e1n\u00ed cen v elektronick\u00e9m obchod\u011b m\u016f\u017ee extrakce dat pomoci v oblasti vlastn\u00edho v\u00fdzkumu, agregace zpr\u00e1v, marketingu, v oblasti nemovitost\u00ed, cestovn\u00edho ruchu, poradenstv\u00ed, financ\u00ed a mnoha dal\u0161\u00edch.<\/p>\n<ul>\n<li><b>Generov\u00e1n\u00ed lead\u016f<\/b><br \/>\nSpole\u010dnosti mohou extrahovat data z katalog\u016f jako Yelp, Crunchbase, Yellowpages a generovat leady pro rozvoj podnik\u00e1n\u00ed. M\u016f\u017eete se pod\u00edvat na video n\u00ed\u017ee, abyste se dozv\u011bd\u011bli, jak extrahovat data z Yellowpages pomoc\u00ed <noindex><a rel=\"nofollow\" href=\"https:\/\/www.octoparse.com\/blog\/big-announcement-web-scraping-template-take-away\">\u0161ablony webov\u00e9ho scraping<\/a><\/noindex>.<\/p>\n<p><center><iframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\/\/embedd.srv.habr.com\/iframe\/5f9016d7d4323713fd415857\" frameborder=\"0\" allowfullscreen=\"\"><\/iframe><\/center><\/li>\n<li><b>Agregace obsahu a zpr\u00e1v<\/b><br \/>\nAgreg\u00e1torov\u00e9 webov\u00e9 str\u00e1nky mohou z\u00edsk\u00e1vat pravideln\u00e9 toky dat z n\u011bkolika zdroj\u016f a udr\u017eovat sv\u00e9 str\u00e1nky aktu\u00e1ln\u00ed.<\/li>\n<li><b>Anal\u00fdza sentimentu<\/b><br \/>\nPo extrakci recenz\u00ed, koment\u00e1\u0159\u016f a hodnocen\u00ed ze soci\u00e1ln\u00edch m\u00e9di\u00ed, jako jsou Instagram a Twitter, mohou specialist\u00e9 analyzovat skryt\u00e9 n\u00e1zory a z\u00edskat p\u0159ehled o tom, jak je vn\u00edm\u00e1na zna\u010dka, produkt nebo n\u011bjak\u00fd jev.<\/li>\n<\/ul>\n<h2>Kroky extrakce dat<\/h2>\n<p>Extrakce dat je prvn\u00edm krokem ETL (zkratka pro Extract, Transform, Load: extrakce, transformace, na\u010d\u00edt\u00e1n\u00ed) a ELT (extrakce, na\u010d\u00edt\u00e1n\u00ed a transformace). ETL a ELT jsou sou\u010d\u00e1st\u00ed komplexn\u00ed strategie integrace dat. Jin\u00fdmi slovy, extrakce dat m\u016f\u017ee b\u00fdt sou\u010d\u00e1st\u00ed jejich t\u011b\u017eby.<\/p>\n<p><img decoding=\"async\" alt=\"Zjist\u00edme, jak\u00fd je rozd\u00edl mezi Data Mining a Data Extraction\" src=\"\/wp-content\/uploads\/2020\/10\/25128c2d46b3bc383606efde5862b480.png\" style=\"display:block;margin: 0 auto;\"><br \/>\nExtrakce, transformace, na\u010d\u00edt\u00e1n\u00ed<\/p>\n<p>Zat\u00edmco data mining je proces z\u00edsk\u00e1v\u00e1n\u00ed informac\u00ed z velk\u00fdch objem\u016f dat, extrakce dat je mnohem krat\u0161\u00ed a jednodu\u0161\u0161\u00ed proces. Lze ji shrnout do t\u0159\u00ed krok\u016f:<\/p>\n<ol>\n<li><b>V\u00fdb\u011br zdroje dat<\/b><br \/>\nVyberte zdroj, ze kter\u00e9ho chcete data extrahovat, nap\u0159\u00edklad webovou str\u00e1nku.<\/li>\n<li><b>Sb\u011br dat<\/b><br \/>\nOde\u0161lete \"GET\" po\u017eadavek na web a analyzujte z\u00edskan\u00fd HTML dokument pomoc\u00ed programovac\u00edch jazyk\u016f, jako jsou Python, PHP, R, Ruby a dal\u0161\u00ed.<\/li>\n<li><b>Ukl\u00e1d\u00e1n\u00ed dat<\/b><br \/>\nUlo\u017ete data do sv\u00e9 m\u00edstn\u00ed datab\u00e1ze nebo do cloudov\u00e9ho \u00falo\u017ei\u0161t\u011b pro budouc\u00ed pou\u017eit\u00ed. Pokud jste zku\u0161en\u00fd program\u00e1tor, kter\u00fd chce data extrahovat, mohou se v\u00e1m v\u00fd\u0161e uveden\u00e9 kroky zd\u00e1t jednoduch\u00e9. Pokud v\u0161ak neprogramujete, existuje zjednodu\u0161en\u00e1 cesta \u2014 pou\u017e\u00edt n\u00e1stroje pro extrakci dat, jako je <noindex><a rel=\"nofollow\" href=\"http:\/\/www.octoparse.com\/\">Octoparse<\/a><\/noindex>. N\u00e1stroje pro extrakci dat, stejn\u011b jako n\u00e1stroje pro data mining, jsou navr\u017eeny tak, aby \u0161et\u0159ily energii a zjednodu\u0161ily zpracov\u00e1n\u00ed dat pro v\u0161echny. Tyto n\u00e1stroje jsou nejen ekonomick\u00e9, ale i u\u017eivatelsky p\u0159\u00edv\u011btiv\u00e9 pro za\u010d\u00e1te\u010dn\u00edky. Umo\u017e\u0148uj\u00ed u\u017eivatel\u016fm shroma\u017e\u010fovat data b\u011bhem n\u011bkolika minut, ukl\u00e1dat je do cloudu a exportovat do mnoha form\u00e1t\u016f: Excel, CSV, HTML, JSON nebo do datab\u00e1z\u00ed na webu p\u0159es API.<\/li>\n<\/ol>\n<h2>Nev\u00fdhody extrakce dat<\/h2>\n<ul>\n<li><b>Selh\u00e1n\u00ed serveru<\/b><br \/>\nP\u0159i extrakci dat ve velk\u00e9m m\u011b\u0159\u00edtku m\u016f\u017ee b\u00fdt webov\u00fd server c\u00edlov\u00e9 str\u00e1nky p\u0159et\u00ed\u017een, co\u017e m\u016f\u017ee v\u00e9st k selh\u00e1n\u00ed serveru. To po\u0161kod\u00ed z\u00e1jmy vlastn\u00edka webu.<\/li>\n<li><b>Blokace podle IP<\/b><br \/>\nKdy\u017e n\u011bkdo p\u0159\u00edli\u0161 \u010dasto sb\u00edr\u00e1 data, webov\u00e9 str\u00e1nky mohou zablokovat jeho IP adresu. Zdroje mohou zcela zak\u00e1zat IP adresu nebo omezit p\u0159\u00edstup, co\u017e zp\u016fsob\u00ed, \u017ee data budou ne\u00fapln\u00e1. Aby bylo mo\u017en\u00e9 data extrahovat a vyhnout se blokaci, je t\u0159eba to prov\u00e1d\u011bt um\u00edrn\u011bnou rychlost\u00ed a pou\u017e\u00edvat n\u011bkter\u00e9 metody proti blokaci.<\/li>\n<li><b>Pr\u00e1vn\u00ed probl\u00e9my<\/b><br \/>\nExtrahov\u00e1n\u00ed dat z webu se nach\u00e1z\u00ed v \u0161ed\u00e9 z\u00f3n\u011b, pokud jde o leg\u00e1lnost. Velk\u00e9 weby, jako je Linkedin a Facebook, jasn\u011b uv\u00e1d\u011bj\u00ed ve sv\u00fdch podm\u00ednk\u00e1ch u\u017eit\u00ed, \u017ee jak\u00e9koli automatizovan\u00e9 extrahov\u00e1n\u00ed dat je zak\u00e1z\u00e1no. Mezi spole\u010dnostmi prob\u011bhlo mnoho soudn\u00edch spor\u016f kv\u016fli \u010dinnosti bot\u016f.<\/li>\n<\/ul>\n<h2>Hlavn\u00ed rozd\u00edly mezi Data Mining a Data Extraction<\/h2>\n<ol>\n<li>Data mining je tak\u00e9 naz\u00fdv\u00e1n objevov\u00e1n\u00edm znalost\u00ed v datab\u00e1z\u00edch, extrakc\u00ed znalost\u00ed, anal\u00fdzou dat\/vzor\u016f a shroma\u017e\u010fov\u00e1n\u00edm informac\u00ed. Data extraction se pou\u017e\u00edv\u00e1 zam\u011bniteln\u011b s extrakc\u00ed webov\u00fdch dat, proch\u00e1zen\u00edm webov\u00fdch str\u00e1nek, shroma\u017e\u010fov\u00e1n\u00edm dat a tak d\u00e1le.<\/li>\n<li>V\u00fdzkum data miningu se p\u0159ev\u00e1\u017en\u011b zam\u011b\u0159uje na strukturovan\u00e1 data, zat\u00edmco p\u0159i extrakci dat se obvykle pracuje s nestrukturovan\u00fdmi nebo \u0161patn\u011b strukturovan\u00fdmi zdroji.<\/li>\n<li>C\u00edlem data miningu je u\u010dinit data u\u017eite\u010dn\u011bj\u0161\u00edmi pro anal\u00fdzu. Data extraction je shroma\u017e\u010fov\u00e1n\u00ed dat na jedno m\u00edsto, kde mohou b\u00fdt ulo\u017eena nebo zpracov\u00e1na.<\/li>\n<li>Anal\u00fdza p\u0159i data miningu se zakl\u00e1d\u00e1 na matematick\u00fdch metod\u00e1ch identifikace vzorc\u016f nebo trend\u016f. Data extraction se op\u00edr\u00e1 o programovac\u00ed jazyky nebo n\u00e1stroje pro extrakci dat k proch\u00e1zen\u00ed zdroj\u016f.<\/li>\n<li>C\u00edlem data miningu je naj\u00edt fakta, kter\u00e1 byla d\u0159\u00edve nezn\u00e1m\u00e1 nebo ignorov\u00e1na, zat\u00edmco data extraction se zab\u00fdv\u00e1 existuj\u00edc\u00edmi informacemi.<\/li>\n<li>Data mining je slo\u017eit\u011bj\u0161\u00ed a vy\u017eaduje v\u011bt\u0161\u00ed investice do v\u00fdcviku lid\u00ed. Data extraction, pokud se pou\u017e\u00edv\u00e1 s vhodn\u00fdm n\u00e1strojem, m\u016f\u017ee b\u00fdt extr\u00e9mn\u011b jednoduch\u00e9 a ekonomick\u00e9.<\/li>\n<\/ol>\n<p>Pom\u00e1h\u00e1me za\u010d\u00e1te\u010dn\u00edk\u016fm se neztratit v Datech. Speci\u00e1ln\u011b pro u\u017eivatele ze St\u0159edn\u00edho webu jsme vytvo\u0159ili promo k\u00f3d <b>HABR<\/b>, kter\u00fd poskytuje dodate\u010dnou slevu 10 % na slevu uvedenou na banneru.<\/p>\n<p><noindex><a rel=\"nofollow\" href=\"https:\/\/skillfactory.ru\/?utm_source=infopartners&amp;utm_medium=habr&amp;utm_campaign=habr_banner&amp;utm_term=regular&amp;utm_content=habr_banner\"><img decoding=\"async\" alt=\"Zjist\u00edme, jak\u00fd je rozd\u00edl mezi Data Mining a Data Extraction\" src=\"\/wp-content\/uploads\/2020\/10\/19f2c89f80e09bcb31702236b2cbc4d2.png\" style=\"display:block;margin: 0 auto;\"><\/a><\/noindex><\/p>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/skillfactory.ru\/dstpro?utm_source=infopartners&amp;utm_medium=habr&amp;utm_campaign=habr_DSPR&amp;utm_term=regular&amp;utm_content=211020\">Vzd\u011bl\u00e1n\u00ed v oboru Data Science od nuly<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" 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href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/507024\">Jak se st\u00e1t Data Scientist bez online kurz\u016f<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/503196\/\">450 bezplatn\u00fdch kurz\u016f od Ivy League<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/510444\/\">Jak studovat Machine Learning 5 dn\u00ed v t\u00fddnu po dobu 9 m\u011bs\u00edc\u016f<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/520540\/\">Kolik vyd\u011bl\u00e1v\u00e1 analytik dat: p\u0159ehled plat\u016f a pracovn\u00edch m\u00edst v Rusku a v zahrani\u010d\u00ed v roce 2020<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/522776\/\">Machine Learning a Computer Vision v t\u011b\u017ea\u0159sk\u00e9m pr\u016fmyslu<\/a><\/noindex><\/li>\n<\/ul>\n<p>Zdroj: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/skillfactory\/blog\/524336\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0414\u0432\u0430 \u044d\u0442\u0438\u0445 \u043c\u043e\u0434\u043d\u044b\u0445 \u0441\u043b\u043e\u0432\u0430, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 Data Science, \u0441\u0431\u0438\u0432\u0430\u044e\u0442 \u0441 \u0442\u043e\u043b\u043a\u0443 \u043c\u043d\u043e\u0433\u0438\u0445 \u043b\u044e\u0434\u0435\u0439. Data Mining \u0447\u0430\u0441\u0442\u043e \u043d\u0435\u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u043f\u043e\u043d\u0438\u043c\u0430\u044e\u0442 \u043a\u0430\u043a \u0438\u0437\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u0435 \u0438 \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u0445, \u043d\u043e \u043d\u0430 \u0441\u0430\u043c\u043e\u043c \u0434\u0435\u043b\u0435 \u0432\u0441\u0435 \u043d\u0430\u043c\u043d\u043e\u0433\u043e \u0441\u043b\u043e\u0436\u043d\u0435\u0435. \u0412 \u044d\u0442\u043e\u043c \u043f\u043e\u0441\u0442\u0435 \u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0440\u0430\u0441\u0441\u0442\u0430\u0432\u0438\u043c \u0442\u043e\u0447\u043a\u0438 \u043d\u0430\u0434 Mining \u0438 \u0432\u044b\u044f\u0441\u043d\u0438\u043c \u0440\u0430\u0437\u043d\u0438\u0446\u0443 \u043c\u0435\u0436\u0434\u0443 Data Mining \u0438 Data Extraction. \u0427\u0442\u043e \u0442\u0430\u043a\u043e\u0435 Data Mining? Data mining, \u0442\u0430\u043a\u0436\u0435 \u043d\u0430\u0437\u044b\u0432\u0430\u0435\u043c\u044b\u0439 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":97891,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-97890","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/cs\/blog\/administrirovanie\/razbiraemsya-v-chem-raznicza-mezhdu-data-mining-i-data-extraction\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.3\" \/>\n\t\t<meta property=\"og:locale\" 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