{"id":550,"date":"2025-12-17T20:01:14","date_gmt":"2025-12-17T17:01:14","guid":{"rendered":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/"},"modified":"2025-12-17T20:01:37","modified_gmt":"2025-12-17T17:01:37","slug":"re-ranking-rag-sistemleri","status":"publish","type":"post","link":"https:\/\/neku.ai\/en\/re-ranking-rag-sistemleri\/","title":{"rendered":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi"},"content":{"rendered":"

Re ranking nedir<\/strong><\/h1>\n
\n

Giri\u015f<\/strong><\/h3>\n

Re ranking, bilgi getirme (retrieval) s\u00fcrecinde sonu\u00e7lar\u0131n yeniden s\u0131ralanmas\u0131 i\u015flemidir. RAG (Retrieval-Augmented Generation) mimarilerinde re ranking, modelin en do\u011fru ba\u011flamsal veriye ula\u015fmas\u0131n\u0131 sa\u011flar. Bu sayede yapay zeka sistemleri, \u00f6zellikle dok\u00fcman i\u015fleme ve vekt\u00f6r arama s\u00fcre\u00e7lerinde daha isabetli yan\u0131tlar \u00fcretir. <\/p>\n

\n

Re ranking nedir tan\u0131m\u0131<\/strong><\/h3>\n

Re ranking; \u00f6nceden getirilen sonu\u00e7lar\u0131n, belirli kriterlere g\u00f6re ikinci bir a\u015famada yeniden derecelendirilmesidir. Basit\u00e7e s\u00f6ylemek gerekirse, ilk arama motoru veya vekt\u00f6r tabanl\u0131 bilgi getirme a\u015famas\u0131 sonu\u00e7lar\u0131 ham olarak sunar; re ranking katman\u0131 ise bu sonu\u00e7lar\u0131 sorgunun niyetine g\u00f6re yeniden de\u011ferlendirir. Bu i\u015flem, \u00f6zellikle RAG tabanl\u0131 sistemlerde yan\u0131t kalitesini \u00f6l\u00e7\u00fclebilir bi\u00e7imde art\u0131r\u0131r.<\/p>\n

\n

re ranking nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

Re ranking a\u015famas\u0131, genellikle iki katmanl\u0131 bir bilgi getirme mimarisi i\u00e7inde yer al\u0131r. \u0130lk katman h\u0131zl\u0131 ve geni\u015f bir sonu\u00e7 k\u00fcmesi d\u00f6nd\u00fcr\u00fcr. \u0130kinci katman, yani re ranking motoru, bu sonu\u00e7lar\u0131 semantik benzerlik, ba\u011flam uygunlu\u011fu ve sorgu ilgisine g\u00f6re s\u0131ralar.<\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n
    \n
  • Skorlama fonksiyonu:<\/strong> \u00c7o\u011funlukla cosine similarity veya \u00f6\u011frenilmi\u015f skor modelidir. <\/li>\n
  • Top-k de\u011feri:<\/strong> \u0130lk getirme a\u015famas\u0131nda ka\u00e7 sonu\u00e7 tutulaca\u011f\u0131n\u0131 belirler. <\/li>\n
  • Re ranking modeli:<\/strong> BERT t\u00fcrevleri veya domain’e \u00f6zel transformer modelleri tercih edilir. <\/li>\n
  • A\u011f\u0131rl\u0131k katsay\u0131lar\u0131:<\/strong> \u0130\u00e7erik t\u00fcr\u00fcne, sorgu yap\u0131s\u0131na veya dok\u00fcman uzunlu\u011funa g\u00f6re ayarlanabilir. <\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n
      \n
    • Top-k se\u00e7iminin \u00e7ok k\u00fc\u00e7\u00fck tutulmas\u0131:<\/strong> Alaka oran\u0131n\u0131 d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
    • Re ranking modelinin a\u015f\u0131r\u0131 karma\u015f\u0131k olmas\u0131:<\/strong> Gecikmeyi art\u0131r\u0131r. <\/li>\n
    • Etiketli veri eksikli\u011fi:<\/strong> \u00d6\u011frenilen s\u0131ralama modelinin tutarl\u0131l\u0131\u011f\u0131n\u0131 zedeler. <\/li>\n<\/ul>\n

      \u00c7\u00f6z\u00fcm olarak, model karma\u015f\u0131kl\u0131\u011f\u0131 ve performans aras\u0131nda denge kurulmal\u0131, s\u00fcrekli test ve \u00f6l\u00e7\u00fcm yap\u0131lmal\u0131d\u0131r.<\/p>\n

      Ger\u00e7ek sistemlerde uygulama \u00f6rnekleri<\/strong><\/h4>\n

      Kurumsal bilgi tabanlar\u0131nda kullan\u0131c\u0131 sorgular\u0131 \u00f6ncelikle vekt\u00f6r arama arac\u0131l\u0131\u011f\u0131yla uygun dok\u00fcmanlarla e\u015fle\u015ftirilir. Ard\u0131ndan re ranking katman\u0131, metin benzerlik puanlar\u0131 ve ba\u011flamsal ipu\u00e7lar\u0131n\u0131 analiz ederek en do\u011fru \u00fc\u00e7 veya be\u015f dok\u00fcman\u0131 se\u00e7er. Bu yakla\u015f\u0131m, kurumsal arama, destek botlar\u0131 ve i\u00e7erik \u00f6neri sistemlerinde s\u0131k\u00e7a uygulan\u0131r.<\/p>\n

      \n

      Teknik a\u00e7\u0131klama (derin seviye)<\/strong><\/h3>\n

      Re ranking s\u00fcreci, basit\u00e7e “getir ve s\u0131rala” mant\u0131\u011f\u0131ndan daha fazlas\u0131d\u0131r. Teknik olarak, embedding\u2019lerle temsil edilen sorgu ve dok\u00fcman vekt\u00f6rleri bir \u00f6n skorlama a\u015famas\u0131ndan ge\u00e7er. Sonras\u0131nda bir yeniden s\u0131ralama modeli, bu adaylar\u0131 ikinci bir katmanda de\u011ferlendirir. <\/p>\n

      Model, genellikle sorgu ve dok\u00fcman \u00e7iftlerini giri\u015f olarak al\u0131r, ba\u011flam uyumu skoru \u00fcretir ve bu skor ile yeni s\u0131ralama olu\u015fturur. B\u00f6ylece bilgi getirme ak\u0131\u015f\u0131 \u00fc\u00e7 a\u015famal\u0131 hale gelir: vekt\u00f6r arama \u2192 re ranking \u2192 cevap \u00fcretimi. Bu yakla\u015f\u0131m RAG sistemlerinde hatal\u0131 ba\u011flam se\u00e7imini minimize eder.<\/p>\n

      \n

      \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
        \n
      • Performans:<\/strong> Yan\u0131t do\u011frulu\u011funu artt\u0131r\u0131r, gereksiz dok\u00fcman \u00e7a\u011f\u0131rmay\u0131 \u00f6nler. <\/li>\n
      • G\u00fcvenilirlik:<\/strong> Bilginin kayna\u011f\u0131n\u0131 daha do\u011fru e\u015fle\u015ftirir, model hal\u00fcsinasyonlar\u0131n\u0131 azalt\u0131r. <\/li>\n
      • Maliyet:<\/strong> Gereksiz sorgu i\u015flemelerini azaltarak altyap\u0131 maliyetini d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
      • \u00d6l\u00e7ekleme:<\/strong> Artan veri hacimlerinde do\u011fruluk kayb\u0131 olmadan sistem geni\u015fler. <\/li>\n
      • Otomasyon:<\/strong> Arama, entegrasyon ve i\u015f ak\u0131\u015flar\u0131nda ak\u0131ll\u0131 s\u0131ralama sa\u011flar. <\/li>\n
      • Karar alma:<\/strong> Do\u011fru bilginin do\u011fru zamanda sunulmas\u0131na imkan tan\u0131r. <\/li>\n
      • Operasyonel verimlilik:<\/strong> Dok\u00fcman tabanl\u0131 s\u00fcre\u00e7lerde yan\u0131t s\u00fcrelerini k\u0131salt\u0131r. <\/li>\n<\/ul>\n
        \n

        Bu kavram NeKu.AI i\u00e7inde nas\u0131l uygulan\u0131r<\/strong><\/h3>\n

        NeKu.AI\u2019nin bilgi taban\u0131 altyap\u0131s\u0131, grounding mimarisi \u00fczerinden bilgi getirme s\u00fcre\u00e7lerini optimize eder. Bu yap\u0131 i\u00e7inde re ranking katman\u0131, getirilen dok\u00fcmanlar\u0131 ba\u011flama g\u00f6re yeniden de\u011ferlendirir. <\/p>\n

        \u00d6rne\u011fin, kullan\u0131c\u0131 belirli bir SAP entegrasyonu hakk\u0131nda sorgu yapt\u0131\u011f\u0131nda sistem \u00f6nce vekt\u00f6r arama ile ilgili teknik makaleleri bulur. Ard\u0131ndan re ranking mod\u00fcl\u00fc, bu sonu\u00e7lar\u0131 kullan\u0131m ba\u011flam\u0131na g\u00f6re i\u015fleyerek en uygun referanslar\u0131 belirler. B\u00f6ylece hem bilgi tutarl\u0131l\u0131\u011f\u0131 hem de model yan\u0131t kalitesi art\u0131r\u0131lm\u0131\u015f olur.<\/p>\n

        \n

        AI geli\u015ftiricileri, veri m\u00fchendisleri i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
          \n
        1. Sorun:<\/strong> RAG tabanl\u0131 bir destek botu, kullan\u0131c\u0131 sorgular\u0131na hatal\u0131 dok\u00fcmanlardan yan\u0131t veriyor. <\/li>\n
        2. Ba\u011flam:<\/strong> Sistem yaln\u0131zca vekt\u00f6r arama sonu\u00e7lar\u0131n\u0131 dikkate al\u0131yor. <\/li>\n
        3. Kavram\u0131n uygulanmas\u0131:<\/strong> Re ranking katman\u0131 eklenerek top-20 sonu\u00e7 yeniden s\u0131ralan\u0131yor. Transformer tabanl\u0131 model, sorgu-dok\u00fcman \u00e7iftleri \u00fczerinden alaka skorlar\u0131 \u00fcretiyor. <\/li>\n
        4. Sonu\u00e7:<\/strong> Bot art\u0131k yaln\u0131zca en alakal\u0131 dok\u00fcmanlar\u0131 yan\u0131t \u00fcretiminde kullan\u0131yor. <\/li>\n
        5. \u0130\u015f etkisi:<\/strong> Yan\u0131t do\u011frulu\u011fu %30 art\u0131yor, kullan\u0131c\u0131 geri bildirimi pozitif y\u00f6nde de\u011fi\u015fiyor. <\/li>\n<\/ol>\n
          \n

          S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n

          Hatalar:<\/strong> <\/p>\n

            \n
          • Re ranking modelini e\u011fitmeden do\u011frudan kullanmak <\/li>\n
          • Farkl\u0131 dok\u00fcman t\u00fcrlerine ayn\u0131 skor fonksiyonunu uygulamak <\/li>\n
          • De\u011ferlendirme metriklerini (nDCG, MRR) izlememek <\/li>\n<\/ul>\n

            En iyi uygulamalar:<\/strong> <\/p>\n

              \n
            • Re ranking modelini d\u00fczenli olarak g\u00fcncellemek <\/li>\n
            • Domain\u2019e \u00f6zg\u00fc etiketlenmi\u015f veriyle ince ayar yapmak <\/li>\n
            • \u0130lk ve ikinci katman sonu\u00e7lar\u0131n\u0131 k\u0131yaslayarak A\/B testleri yapmak <\/li>\n
            • D\u00fc\u015f\u00fck gecikmeli modelleri tercih etmek <\/li>\n<\/ul>\n
              \n

              Sonu\u00e7<\/strong><\/h3>\n

              Re ranking, RAG tabanl\u0131 yapay zeka sistemlerinde bilgi getirme do\u011frulu\u011funu belirleyen kritik bir bile\u015fendir. Do\u011fru uyguland\u0131\u011f\u0131nda dok\u00fcman i\u015fleme, vekt\u00f6r arama ve yan\u0131t \u00fcretimi zincirinin kalitesini \u00f6l\u00e7\u00fclebilir bi\u00e7imde y\u00fckseltir. <\/p>\n

              NeKu.AI gibi geli\u015fmi\u015f bilgi taban\u0131 ve grounding mimarilerine sahip sistemler, re ranking arac\u0131l\u0131\u011f\u0131yla hem teknik derinlik hem de operasyonel verimlilik sa\u011flar. Bu yakla\u015f\u0131m modern AI \u00e7\u00f6z\u00fcmlerinde do\u011fruluk, h\u0131z ve ba\u011flamsal g\u00fcvenilirli\u011fi bir arada sunar.<\/p>","protected":false},"excerpt":{"rendered":"

              Re ranking nedir Giri\u015f Re ranking, bilgi getirme (retrieval) s\u00fcrecinde sonu\u00e7lar\u0131n yeniden s\u0131ralanmas\u0131 i\u015flemidir. RAG (Retrieval-Augmented Generation) mimarilerinde re ranking, modelin en do\u011fru ba\u011flamsal veriye ula\u015fmas\u0131n\u0131 [\u2026]<\/span><\/p>\n","protected":false},"author":2,"featured_media":551,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[],"tags":[],"class_list":["post-550","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"\nRAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/neku.ai\/en\/re-ranking-rag-sistemleri\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI\" \/>\n<meta property=\"og:description\" content=\"Re ranking nedir Giri\u015f Re ranking, bilgi getirme (retrieval) s\u00fcrecinde sonu\u00e7lar\u0131n yeniden s\u0131ralanmas\u0131 i\u015flemidir. RAG (Retrieval-Augmented Generation) mimarilerinde re ranking, modelin en do\u011fru ba\u011flamsal veriye ula\u015fmas\u0131n\u0131 [\u2026]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/neku.ai\/en\/re-ranking-rag-sistemleri\/\" \/>\n<meta property=\"og:site_name\" content=\"NeKu.AI\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-17T17:01:14+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-17T17:01:37+00:00\" \/>\n<meta name=\"author\" content=\"Serkan \u00d6zcan\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Serkan \u00d6zcan\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/\"},\"author\":{\"name\":\"Serkan \u00d6zcan\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/person\\\/cf640cfda3e16635fb740662d943e96b\"},\"headline\":\"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi\",\"datePublished\":\"2025-12-17T17:01:14+00:00\",\"dateModified\":\"2025-12-17T17:01:37+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/\"},\"wordCount\":969,\"publisher\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/cover-image-550.jpg\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/\",\"url\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/\",\"name\":\"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/cover-image-550.jpg\",\"datePublished\":\"2025-12-17T17:01:14+00:00\",\"dateModified\":\"2025-12-17T17:01:37+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#primaryimage\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/cover-image-550.jpg\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/cover-image-550.jpg\",\"width\":1024,\"height\":1024},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/neku.ai\\\/re-ranking-rag-sistemleri\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Anasayfa\",\"item\":\"https:\\\/\\\/neku.ai\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#website\",\"url\":\"https:\\\/\\\/neku.ai\\\/\",\"name\":\"NeKuAI\",\"description\":\"\u0130\u015fletmenizi daha "Ak\u0131ll\u0131" yap\u0131n\",\"publisher\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/neku.ai\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\",\"name\":\"NeKuAI\",\"url\":\"https:\\\/\\\/neku.ai\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/02\\\/apple-icon-180x180-1.png\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/02\\\/apple-icon-180x180-1.png\",\"width\":180,\"height\":180,\"caption\":\"NeKuAI\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/logo\\\/image\\\/\"}},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/person\\\/cf640cfda3e16635fb740662d943e96b\",\"name\":\"Serkan \u00d6zcan\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"url\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"contentUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/plugins\\\/swiss-toolkit-for-wp\\\/\\\/admin\\\/img\\\/default-avatar.png\",\"caption\":\"Serkan \u00d6zcan\"},\"url\":\"https:\\\/\\\/neku.ai\\\/en\\\/author\\\/serkanozcan\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/neku.ai\/en\/re-ranking-rag-sistemleri\/","og_locale":"en_US","og_type":"article","og_title":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI","og_description":"Re ranking nedir Giri\u015f Re ranking, bilgi getirme (retrieval) s\u00fcrecinde sonu\u00e7lar\u0131n yeniden s\u0131ralanmas\u0131 i\u015flemidir. RAG (Retrieval-Augmented Generation) mimarilerinde re ranking, modelin en do\u011fru ba\u011flamsal veriye ula\u015fmas\u0131n\u0131 [\u2026]","og_url":"https:\/\/neku.ai\/en\/re-ranking-rag-sistemleri\/","og_site_name":"NeKu.AI","article_published_time":"2025-12-17T17:01:14+00:00","article_modified_time":"2025-12-17T17:01:37+00:00","author":"Serkan \u00d6zcan","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Serkan \u00d6zcan","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#article","isPartOf":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/"},"author":{"name":"Serkan \u00d6zcan","@id":"https:\/\/neku.ai\/#\/schema\/person\/cf640cfda3e16635fb740662d943e96b"},"headline":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi","datePublished":"2025-12-17T17:01:14+00:00","dateModified":"2025-12-17T17:01:37+00:00","mainEntityOfPage":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/"},"wordCount":969,"publisher":{"@id":"https:\/\/neku.ai\/#organization"},"image":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#primaryimage"},"thumbnailUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/12\/cover-image-550.jpg","inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/","url":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/","name":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi - NeKu.AI","isPartOf":{"@id":"https:\/\/neku.ai\/#website"},"primaryImageOfPage":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#primaryimage"},"image":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#primaryimage"},"thumbnailUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/12\/cover-image-550.jpg","datePublished":"2025-12-17T17:01:14+00:00","dateModified":"2025-12-17T17:01:37+00:00","breadcrumb":{"@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/neku.ai\/re-ranking-rag-sistemleri\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#primaryimage","url":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/12\/cover-image-550.jpg","contentUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/12\/cover-image-550.jpg","width":1024,"height":1024},{"@type":"BreadcrumbList","@id":"https:\/\/neku.ai\/re-ranking-rag-sistemleri\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Anasayfa","item":"https:\/\/neku.ai\/"},{"@type":"ListItem","position":2,"name":"RAG tabanli yapay zeka sistemlerinde re ranking ile dogruluk artisi"}]},{"@type":"WebSite","@id":"https:\/\/neku.ai\/#website","url":"https:\/\/neku.ai\/","name":"NeKuAI","description":"\u0130\u015fletmenizi daha "Ak\u0131ll\u0131" yap\u0131n","publisher":{"@id":"https:\/\/neku.ai\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/neku.ai\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/neku.ai\/#organization","name":"NeKuAI","url":"https:\/\/neku.ai\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/#\/schema\/logo\/image\/","url":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/02\/apple-icon-180x180-1.png","contentUrl":"https:\/\/neku.ai\/wp-content\/uploads\/2025\/02\/apple-icon-180x180-1.png","width":180,"height":180,"caption":"NeKuAI"},"image":{"@id":"https:\/\/neku.ai\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/neku.ai\/#\/schema\/person\/cf640cfda3e16635fb740662d943e96b","name":"Serkan \u00d6zcan","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","url":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","contentUrl":"https:\/\/neku.ai\/wp-content\/plugins\/swiss-toolkit-for-wp\/\/admin\/img\/default-avatar.png","caption":"Serkan \u00d6zcan"},"url":"https:\/\/neku.ai\/en\/author\/serkanozcan\/"}]}},"_links":{"self":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts\/550","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/comments?post=550"}],"version-history":[{"count":0,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/posts\/550\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/media\/551"}],"wp:attachment":[{"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/media?parent=550"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/categories?post=550"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/neku.ai\/en\/wp-json\/wp\/v2\/tags?post=550"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}