{"id":2605,"date":"2019-12-05T16:40:33","date_gmt":"2019-12-05T21:40:33","guid":{"rendered":"http:\/\/skimai.com\/?p=2605"},"modified":"2024-05-20T07:38:37","modified_gmt":"2024-05-20T12:38:37","slug":"themenmodellierung-fur-produktmanager","status":"publish","type":"post","link":"https:\/\/skimai.com\/de\/topic-modeling-for-product-managers\/","title":{"rendered":"Themenmodellierung f\u00fcr Produktmanager"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_1 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Inhalts\u00fcbersicht<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Inhaltsverzeichnis umschalten\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Umschalten auf<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/skimai.com\/de\/topic-modeling-for-product-managers\/#Topic_Modeling_for_Product_Managers\" >Themenmodellierung f\u00fcr Produktmanager<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/skimai.com\/de\/topic-modeling-for-product-managers\/#What_is_Topic_Modeling\" >Was ist Topic Modeling?<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/skimai.com\/de\/topic-modeling-for-product-managers\/#The_Difference_Between_Unsupervised_vs_Supervised_Learning\" >Der Unterschied zwischen un\u00fcberwachtem und \u00fcberwachtem Lernen<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/skimai.com\/de\/topic-modeling-for-product-managers\/#The_Benefits_of_Supervised_Learning_for_Product_Managers\" >Die Vorteile des \u00fcberwachten Lernens f\u00fcr Produktmanager<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"Topic_Modeling_for_Product_Managers\"><\/span>Themenmodellierung f\u00fcr Produktmanager<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<pre><code>        <h1><span class=\"ez-toc-section\" id=\"What_is_Topic_Modeling\"><\/span>Was ist Topic Modeling?<span class=\"ez-toc-section-end\"><\/span><\/h1>        \n    Die Themenmodellierung ist eine Art der nat\u00fcrlichen Sprachverarbeitung (NLP), die dazu dient, \"Themen\" oder h\u00e4ufig vorkommende W\u00f6rter oder Wortgruppen in einer Reihe von Dokumenten zu finden. Themenmodelle sind f\u00fcr Produktmanager von entscheidender Bedeutung, da sie es ihnen erm\u00f6glichen, die riesigen Mengen an Textdaten, mit denen sie arbeiten m\u00fcssen, zu sortieren und zu analysieren. Produktmanager ben\u00f6tigen Themenmodelle f\u00fcr verschiedene Aufgaben, wie z. B.:<\/p><ul><li>Analyse einer gro\u00dfen Anzahl von Bewertungen, um zu erfahren, was die Kunden \u00fcber ihre Produkte sagen.<\/li><li>Verstehen, \u00fcber welche Produktmerkmale die Kunden sprechen.<\/li><li>Gewinnung von Erkenntnissen dar\u00fcber, welche neuen Funktionen die Kunden w\u00fcnschen.<\/li><li>\u00dcber die sozialen Medien die Meinung der Kunden \u00fcber ihr Produkt erfahren.<\/li><\/ul><p>In gewisser Weise \u00e4hnelt die Themenmodellierung der Stimmungsmodellierung: Beide sind NLP-Algorithmen zur Analyse gro\u00dfer Textmengen. W\u00e4hrend Stimmungsmodelle zu bestimmen versuchen, ob ein Text positiv oder negativ ist, versuchen Themenmodelle zu bestimmen, worum es in einem Text geht. Themenmodelle arbeiten, indem sie eine Reihe von Dokumenten nach den am h\u00e4ufigsten vorkommenden W\u00f6rtern oder Phrasen in jedem Dokument durchsuchen und dann eine Kreuzkorrelation durchf\u00fchren, um festzustellen, welche W\u00f6rter und Phrasen sowohl in jedem Dokument als auch in allen Dokumenten am h\u00e4ufigsten vorkommen. Da wir die Themenmodellierung speziell f\u00fcr Produktmanager untersuchen, ist es wichtig, sich mit der Art des Lernens zu befassen, die angewendet werden sollte.<\/p>       \n        <h2><span class=\"ez-toc-section\" id=\"The_Difference_Between_Unsupervised_vs_Supervised_Learning\"><\/span>Der Unterschied zwischen un\u00fcberwachtem und \u00fcberwachtem Lernen<span class=\"ez-toc-section-end\"><\/span><\/h2>        \n    <p>Die meisten Algorithmen zur Themenmodellierung werden mit un\u00fcberwachtem Lernen trainiert. \"Un\u00fcberwacht\" bedeutet einfach, dass der Algorithmus auf einer gro\u00dfen Menge von unbeschrifteten Daten trainiert wird. Un\u00fcberwachtes Lernen bietet viele Vorteile:<\/p><ul><li>Kurze Einarbeitungs- und Berechnungszeit.<\/li><li>Robuste Themenauswahl, die nicht durch vordefinierte Themen eingeschr\u00e4nkt ist.<\/li><li>H\u00f6here Modellgenauigkeit beim Auffinden aller relevanten Themen.<\/li><\/ul><p>Trotz seiner Vorteile kann un\u00fcberwachtes Lernen jedoch bei der Analyse von Daten \u00fcber ein bestimmtes Produkt zu Genauigkeitsverlusten oder sogar zu ungenauen oder nicht relevanten Ergebnissen f\u00fchren.<\/code><\/pre>\n<p>\u00a0<\/p>\n<p>Im Gegensatz zum un\u00fcberwachten Lernen wird beim \u00fcberwachten Lernen das Themenmodell anhand markierter Daten trainiert. Das hei\u00dft, es wird ein Satz von Themen ausgew\u00e4hlt, die der Algorithmus erkennen soll. Bei dieser Art des Lernens wird dem Themenmodell eine Reihe vorgegebener Themen vorgegeben, nach denen es suchen soll. Das \u00fcberwachte Lernen hat zwar den Nachteil, dass es zeitaufw\u00e4ndiger ist und die Gefahr besteht, dass wichtige Themen, die nicht ausgew\u00e4hlt wurden, \u00fcbersehen werden, aber es hat auch seine eigenen gro\u00dfen Vorteile:<\/p>\n<ul>\n<li>Die M\u00f6glichkeit, nach bestimmten Themen zu suchen.<\/li>\n<li>Die M\u00f6glichkeit zu w\u00e4hlen, nach wie vielen Themen gesucht werden soll.<\/li>\n<li>H\u00f6here Modellgenauigkeit bei der Suche nach den richtigen Themen.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"The_Benefits_of_Supervised_Learning_for_Product_Managers\"><\/span>Die Vorteile des \u00fcberwachten Lernens f\u00fcr Produktmanager<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code>    <p>Betrachtet man das Themenlernen f\u00fcr Produktmanager, so ist die effektivste Art des Trainings f\u00fcr ihre Themenmodelle das \u00fcberwachte Lernen. F\u00fcr das Verfassen einer Forschungsarbeit beispielsweise ist un\u00fcberwachtes Lernen optimal, da es die h\u00e4ufigsten Themen und den Kontext, in dem sie verwendet werden, entdeckt. Andererseits wei\u00df ein Produktmanager bereits, nach welchen Themen er suchen muss. Ein Produktmanager braucht kein allgemeines Wissen \u00fcber die Themen der Dokumente, sondern muss Daten finden, die f\u00fcr sein Produkt spezifisch sind. Ein Produktmanager wei\u00df in der Regel bereits, welche Informationen er \u00fcber sein Produkt ben\u00f6tigt, und wird die n\u00fctzlichsten Daten aus einem Themenmodell gewinnen, indem er es auf diese Informationen trainiert. Die Vorteile der Verwendung von \u00fcberwachtem Lernen f\u00fcr die Themenmodellierung f\u00fcr Produktmanager sind:<\/p><ul><li>\u00dcberwachtes Lernen liefert bessere Ergebnisse bei der Arbeit mit Industrie- und Nachrichtendokumenten.<\/li><li>Das \u00fcberwachte Lernen beschr\u00e4nkt den Umfang der modellierten Themen auf die Themen, die sich auf das spezifische Produkt beziehen.<\/li><li>\u00dcberwachtes Lernen f\u00fchrt zu Themen, die f\u00fcr den Anwendungsfall des Produktmanagers relevant sind, wie z. B. die Themen der Rezensionen im Vergleich zu den Themen der Funktionen.<\/li><\/ul><p>Zusammenfassend l\u00e4sst sich sagen, dass Themenmodelle einen NLP-Algorithmus zum Auffinden der h\u00e4ufigsten W\u00f6rter und Ausdr\u00fccke in einer gro\u00dfen Menge von Dokumenten darstellen. Themenmodelle k\u00f6nnen durch un\u00fcberwachtes und \u00fcberwachtes Lernen trainiert werden. Obwohl beide Arten des Lernens ihre Vorteile haben, profitieren Produktmanager bei der Themenmodellierung am meisten von der Verwendung des \u00fcberwachten Lernens f\u00fcr ihre Themenmodelle.<\/code><\/pre>\n<p>\u00a0<\/p>\n<p>Sind Sie bereit f\u00fcr die ersten Schritte? Lesen Sie unseren Beitrag \u00fcber <a href=\"http:\/\/skimai.com\/de\/10-bewahrte-verfahren-fur-die-speicherung-gekennzeichneter-daten\/\">10 Best Practices f\u00fcr die Speicherung beschrifteter Daten<\/a> um sicherzustellen, dass Sie einen soliden, gut organisierten Datensatz f\u00fcr Ihr \u00fcberwachtes Themenmodell haben.<\/p>","protected":false},"excerpt":{"rendered":"<p>Topic Modeling for Product Managers What is Topic Modeling? Topic modeling is a type of natural language processing (NLP) used to find \u201ctopics,\u201d or commonly occurring words or groups of words, within a set of documents. Topic models are critical to product managers because they enable them to sort and analyze the huge amounts of [&hellip;]<\/p>\n","protected":false},"author":1003,"featured_media":2610,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-custom-post-template.php","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[125,67,78],"tags":[79,75,91],"class_list":["post-2605","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-enterprise-ai-blog","category-ml-nlp","category-ai-project-management","tag-how-to","tag-nlp","tag-topic-modeling"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Topic Modeling for Product Managers - A Beginner&#039;s Guide - by Skim AI<\/title>\n<meta name=\"description\" content=\"&quot;How to&quot; guide for project managers that want to use Topic Modeling to make sense of data by organizing and categorizing data into topics\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/skimai.com\/de\/themenmodellierung-fur-produktmanager\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Topic Modeling for Product Managers - A Beginner&#039;s Guide - by Skim AI\" \/>\n<meta property=\"og:description\" content=\"&quot;How to&quot; guide for project managers that want to use Topic Modeling to make sense of data by organizing and categorizing data into topics\" \/>\n<meta property=\"og:url\" content=\"https:\/\/skimai.com\/de\/themenmodellierung-fur-produktmanager\/\" \/>\n<meta property=\"og:site_name\" content=\"Skim AI\" \/>\n<meta property=\"article:published_time\" content=\"2019-12-05T21:40:33+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-05-20T12:38:37+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/skimai.com\/wp-content\/uploads\/2019\/12\/topic-modeling-for-product-managers.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2999\" \/>\n\t<meta property=\"og:image:height\" content=\"1999\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Greggory Elias\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Verfasst von\" \/>\n\t<meta name=\"twitter:data1\" content=\"Greggory Elias\" \/>\n\t<meta name=\"twitter:label2\" content=\"Gesch\u00e4tzte Lesezeit\" \/>\n\t<meta name=\"twitter:data2\" content=\"3\u00a0Minuten\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/\"},\"author\":{\"name\":\"Greggory Elias\",\"@id\":\"https:\/\/skimai.com\/uk\/#\/schema\/person\/7a883b4a2d2ea22040f42a7975eb86c6\"},\"headline\":\"Topic Modeling for Product Managers\",\"datePublished\":\"2019-12-05T21:40:33+00:00\",\"dateModified\":\"2024-05-20T12:38:37+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/\"},\"wordCount\":150,\"publisher\":{\"@id\":\"https:\/\/skimai.com\/uk\/#organization\"},\"image\":{\"@id\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/skimai.com\/wp-content\/uploads\/2019\/12\/topic-modeling-for-product-managers.jpg\",\"keywords\":[\"how to\",\"nlp\",\"topic modeling\"],\"articleSection\":[\"Enterprise AI\",\"LLMs \/ NLP\",\"Project Management\"],\"inLanguage\":\"de\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/\",\"url\":\"https:\/\/skimai.com\/topic-modeling-for-product-managers\/\",\"name\":\"Topic Modeling for Product Managers - 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