{"id":590,"date":"2025-12-23T08:00:20","date_gmt":"2025-12-23T05:00:20","guid":{"rendered":"https:\/\/neku.ai\/bm25-rag-ve-vektor-arama\/"},"modified":"2025-12-23T08:01:22","modified_gmt":"2025-12-23T05:01:22","slug":"bm25-rag-ve-vektor-arama","status":"publish","type":"post","link":"https:\/\/neku.ai\/en\/bm25-rag-ve-vektor-arama\/","title":{"rendered":"BM25 ile RAG ve Vekt\u00f6r Aramada Dogruluk Artisi"},"content":{"rendered":"

BM25 nedir<\/strong><\/h1>\n
\n

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

BM25, bilgi getirme (information retrieval) sistemlerinde en \u00e7ok kullan\u0131lan s\u0131ralama algoritmalar\u0131ndan biridir. Arama sonu\u00e7lar\u0131n\u0131n kullan\u0131c\u0131 sorgusu ile ne kadar ilgili oldu\u011funu \u00f6l\u00e7mek i\u00e7in tasarlanm\u0131\u015ft\u0131r. RAG (Retrieval Augmented Generation) mimarilerinde, \u00f6zellikle dok\u00fcman i\u015fleme ve vekt\u00f6r arama s\u00fcre\u00e7lerinde, BM25 b\u00fcy\u00fck bir rol oynar \u00e7\u00fcnk\u00fc kelime temelli metin e\u015fle\u015ftirmesinde istatistiksel bir do\u011fruluk sa\u011flar.<\/p>\n

\n

BM25 nedir tan\u0131m\u0131<\/strong><\/h3>\n

BM25, \u201cBest Matching 25\u201d ad\u0131n\u0131 ta\u015f\u0131yan ve klasik TF-IDF (Term Frequency – Inverse Document Frequency) y\u00f6nteminin geli\u015ftirilmi\u015f bir t\u00fcrevidir. Temel olarak, bir sorguda ge\u00e7en kelimelerin her dok\u00fcmanda ne kadar \u00f6nemli oldu\u011funu hesaplayarak dok\u00fcmanlar\u0131 s\u0131ralar. Ana amac\u0131, kelimenin metin i\u00e7erisindeki s\u0131kl\u0131\u011f\u0131n\u0131 dengeli bir bi\u00e7imde hesaplamak ve uzun dok\u00fcmanlar\u0131n haks\u0131z avantaj sa\u011flamas\u0131n\u0131n \u00f6n\u00fcne ge\u00e7mektir.<\/p>\n

\n

bm25 nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

BM25, sorgu kelimeleri ile dok\u00fcman i\u00e7eri\u011fi aras\u0131nda olas\u0131l\u0131ksal bir skor hesaplar. Bu skor, kelime s\u0131kl\u0131\u011f\u0131, dok\u00fcman uzunlu\u011fu ve genel kelime da\u011f\u0131l\u0131m\u0131na g\u00f6re dengelenir. Arama sistemleri, her dok\u00fcman i\u00e7in bu skoru hesaplar ve en y\u00fcksek skor alan dok\u00fcmanlar\u0131 kullan\u0131c\u0131ya sunar.<\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n

BM25\u2019in ana parametreleri k1<\/strong> ve b<\/strong>\u2019dir. <\/p>\n

    \n
  • k1<\/strong> terim s\u0131kl\u0131\u011f\u0131na ne kadar a\u011f\u0131rl\u0131k verilece\u011fini belirler. Genelde 1.2 ila 2.0 aras\u0131nda bir de\u011fer kullan\u0131l\u0131r. <\/li>\n
  • b<\/strong>, dok\u00fcman uzunlu\u011funu ne \u00f6l\u00e7\u00fcde normalize edece\u011fini ayarlayan parametredir. 0 de\u011feri uzunluk etkisini yok sayar, 1 de\u011feri tamamen normalize eder.
    \nBu parametreler, arama indeksinin do\u011fas\u0131na g\u00f6re test edilip optimize edilmelidir.<\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n

    Bir\u00e7ok uygulama, k1 ve b parametrelerini varsay\u0131lan de\u011ferlerde b\u0131rak\u0131r; bu, \u00f6zel veri k\u00fcmelerinde performans d\u00fc\u015f\u00fckl\u00fc\u011f\u00fcne yol a\u00e7abilir. Ayr\u0131ca \u00f6n i\u015fleme ad\u0131mlar\u0131nda stop word\u2019lerin (\u00f6nemsiz kelimeler) temizlenmemesi, BM25 skorlar\u0131n\u0131 olumsuz etkiler. Bu nedenle indeksleme \u00f6ncesi kelime k\u00f6klerini \u00e7\u0131karma ve gereksiz kelimeleri filtreleme \u00f6nerilir.<\/p>\n

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

    Apache Lucene, Elasticsearch ve Solr gibi arama motorlar\u0131 BM25\u2019i varsay\u0131lan s\u0131ralama algoritmas\u0131 olarak kullan\u0131r. Ayn\u0131 \u015fekilde, RAG tabanl\u0131 sistemlerde vekt\u00f6r arama ile birlikte \u00e7al\u0131\u015farak hem semantik hem istatistiksel e\u015fle\u015fme sa\u011flar. NeKu.AI gibi bilgi taban\u0131 sistemlerinde de BM25 \u00e7\u0131kt\u0131s\u0131, vekt\u00f6r temelli benzerlik skorlar\u0131yla birle\u015ftirilerek sonu\u00e7 do\u011frulu\u011fu art\u0131r\u0131l\u0131r.<\/p>\n

    \n

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

    BM25\u2019in i\u015fleyi\u015fi ad\u0131m ad\u0131m \u015fu \u015fekildedir: <\/p>\n

      \n
    1. Her dok\u00fcmandaki terim s\u0131kl\u0131\u011f\u0131 hesaplan\u0131r. <\/li>\n
    2. Dok\u00fcman uzunlu\u011fu ortalama uzunluk ile kar\u015f\u0131la\u015ft\u0131r\u0131larak normalize edilir. <\/li>\n
    3. Her terim i\u00e7in IDF de\u011feri hesaplan\u0131r ve global kelime yayg\u0131nl\u0131\u011f\u0131 hesaba kat\u0131l\u0131r. <\/li>\n
    4. Bu veriler, BM25 form\u00fcl\u00fcne eklenerek bir skor \u00fcretir.
      \nBu skor, RAG tabanl\u0131 sorgularda dok\u00fcman geri getirme a\u015famas\u0131nda kullan\u0131l\u0131r. \u00d6zellikle b\u00fcy\u00fck dok\u00fcman havuzlar\u0131nda BM25, y\u00fcksek do\u011fruluklu bilgi getirme sa\u011flar ve vekt\u00f6r arama modelleriyle hibrit bir yap\u0131 olu\u015fturur.<\/li>\n<\/ol>\n
      \n

      \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
        \n
      • Performans:<\/strong> Metin e\u015fle\u015ftirmelerini optimize eder, arama gecikmesini azalt\u0131r. <\/li>\n
      • G\u00fcvenilirlik:<\/strong> Tutarl\u0131 ve istatistiksel olarak anlaml\u0131 sonu\u00e7lar verir. <\/li>\n
      • Maliyet:<\/strong> Hesaplama ve veri saklama a\u00e7\u0131s\u0131ndan TF-IDF\u2019e g\u00f6re daha verimlidir. <\/li>\n
      • \u00d6l\u00e7ekleme:<\/strong> B\u00fcy\u00fck veri k\u00fcmelerinde kolayca uyarlanabilir. <\/li>\n
      • Otomasyon:<\/strong> Bilgi y\u00f6nlendirme s\u00fcre\u00e7lerinde manuel do\u011frulama ihtiyac\u0131n\u0131 azalt\u0131r. <\/li>\n
      • Karar alma:<\/strong> Do\u011fru bilgiyi h\u0131zl\u0131 eri\u015fimle sunarak daha isabetli karar deste\u011fi sa\u011flar. <\/li>\n
      • Operasyonel verimlilik:<\/strong> Arama ve bilgi g\u00fcncelleme s\u00fcre\u00e7lerini otomatik hale getirir.<\/li>\n<\/ul>\n
        \n

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

        NeKu.AI, bilgi taban\u0131 ve grounding mimarisinde hem vekt\u00f6r arama hem BM25 s\u0131ralama mekanizmas\u0131n\u0131 kullan\u0131r. Dok\u00fcmanlar\u0131n semantik i\u00e7eri\u011fi vekt\u00f6r uzay\u0131nda de\u011ferlendirilirken, BM25 metin frekans\u0131ndaki istatistiksel a\u011f\u0131rl\u0131klar\u0131 hesaba katar. Bu kombinasyon, RAG s\u00fcrecinde modelin en do\u011fru ba\u011flaml\u0131 cevab\u0131 \u00fcretmesini sa\u011flar. \u00d6zellikle SAP entegrasyonlar\u0131nda, metin bazl\u0131 veri geri getirme s\u00fcre\u00e7lerinde BM25 altyap\u0131s\u0131 otomasyonu destekler.<\/p>\n

        \n

        AI geli\u015ftiricileri, veri m\u00fchendisleri i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
          \n
        1. Sorun:<\/strong> Bir firma SAP sistemindeki metin raporlar\u0131ndan do\u011fru i\u00e7g\u00f6r\u00fcy\u00fc bulmakta zorlan\u0131yor. <\/li>\n
        2. Ba\u011flam:<\/strong> RAG tabanl\u0131 bilgi getirme sistemi kurmak istiyor. <\/li>\n
        3. Kavram\u0131n uygulanmas\u0131:<\/strong> NeKu.AI altyap\u0131s\u0131nda dok\u00fcman indeksi BM25 ile olu\u015fturuluyor. Vekt\u00f6r arama, semantik benzerli\u011fi bulurken BM25 s\u0131ralama metin i\u00e7i ilgiyi hesapl\u0131yor. <\/li>\n
        4. Sonu\u00e7:<\/strong> Sorgular hem anlam hem frekans a\u00e7\u0131s\u0131ndan en uygun veriyi getiriyor. <\/li>\n
        5. \u0130\u015f etkisi:<\/strong> Bilgi eri\u015fimi h\u0131zlan\u0131yor, otomatik raporlama ve karar alma s\u00fcre\u00e7leri iyile\u015fiyor.<\/li>\n<\/ol>\n
          \n

          S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n
            \n
          • Parametre optimizasyonu yap\u0131lmadan varsay\u0131lan de\u011ferlere g\u00fcvenmek hatal\u0131d\u0131r. <\/li>\n
          • \u00d6n i\u015fleme ad\u0131mlar\u0131nda yanl\u0131\u015f tokenizasyon, skor do\u011frulu\u011funu d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
          • BM25 ve vekt\u00f6r aramay\u0131 ayn\u0131 mimaride dengeli bi\u00e7imde kullanmak en iyi sonu\u00e7lar\u0131 sa\u011flar. <\/li>\n
          • Ger\u00e7ek sistemlerde s\u00fcrekli performans izleme ve indeks yenileme kritik \u00f6nemdedir. <\/li>\n
          • K\u00fc\u00e7\u00fck veri k\u00fcmelerinde b parametresini azaltmak, a\u015f\u0131r\u0131 normalize hatalar\u0131ndan ka\u00e7\u0131n\u0131r.<\/li>\n<\/ul>\n
            \n

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

            BM25, modern bilgi getirme sistemlerinin temelini olu\u015fturan g\u00fc\u00e7l\u00fc bir algoritmad\u0131r. RAG, dok\u00fcman i\u015fleme ve vekt\u00f6r arama s\u00fcre\u00e7lerinde performans ve do\u011fruluk a\u00e7\u0131s\u0131ndan kritik rol oynar. NeKu.AI gibi kurumsal platformlarda BM25\u2019in kullan\u0131m\u0131, bilgiye eri\u015fimi h\u0131zland\u0131r\u0131p karar destek sistemlerinin isabetini art\u0131r\u0131r. Do\u011fru parametrelendirme ve hibrit entegrasyon, BM25\u2019in de\u011ferini tam olarak ortaya \u00e7\u0131kar\u0131r.<\/p>","protected":false},"excerpt":{"rendered":"

            BM25 nedir Giri\u015f BM25, bilgi getirme (information retrieval) sistemlerinde en \u00e7ok kullan\u0131lan s\u0131ralama algoritmalar\u0131ndan biridir. Arama sonu\u00e7lar\u0131n\u0131n kullan\u0131c\u0131 sorgusu ile ne kadar ilgili oldu\u011funu \u00f6l\u00e7mek i\u00e7in [\u2026]<\/span><\/p>\n","protected":false},"author":2,"featured_media":591,"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-590","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"\nBM25 ile RAG ve Vekt\u00f6r Aramada 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\/bm25-rag-ve-vektor-arama\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BM25 ile RAG ve Vekt\u00f6r Aramada Dogruluk Artisi - NeKu.AI\" \/>\n<meta property=\"og:description\" content=\"BM25 nedir Giri\u015f BM25, bilgi getirme (information retrieval) sistemlerinde en \u00e7ok kullan\u0131lan s\u0131ralama algoritmalar\u0131ndan biridir. Arama sonu\u00e7lar\u0131n\u0131n kullan\u0131c\u0131 sorgusu ile ne kadar ilgili oldu\u011funu \u00f6l\u00e7mek i\u00e7in [\u2026]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/neku.ai\/en\/bm25-rag-ve-vektor-arama\/\" \/>\n<meta property=\"og:site_name\" content=\"NeKu.AI\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-23T05:00:20+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-23T05:01:22+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\\\/bm25-rag-ve-vektor-arama\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/bm25-rag-ve-vektor-arama\\\/\"},\"author\":{\"name\":\"Serkan \u00d6zcan\",\"@id\":\"https:\\\/\\\/neku.ai\\\/#\\\/schema\\\/person\\\/cf640cfda3e16635fb740662d943e96b\"},\"headline\":\"BM25 ile RAG ve Vekt\u00f6r Aramada Dogruluk Artisi\",\"datePublished\":\"2025-12-23T05:00:20+00:00\",\"dateModified\":\"2025-12-23T05:01:22+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/bm25-rag-ve-vektor-arama\\\/\"},\"wordCount\":976,\"publisher\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/neku.ai\\\/bm25-rag-ve-vektor-arama\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/neku.ai\\\/wp-content\\\/uploads\\\/2025\\\/12\\\/cover-image-590.jpg\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/neku.ai\\\/bm25-rag-ve-vektor-arama\\\/\",\"url\":\"https:\\\/\\\/neku.ai\\\/bm25-rag-ve-vektor-arama\\\/\",\"name\":\"BM25 ile RAG ve Vekt\u00f6r Aramada Dogruluk Artisi - 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