{"id":477994,"date":"2023-08-09T09:25:37","date_gmt":"2023-08-09T09:25:37","guid":{"rendered":""},"modified":"2023-09-05T11:15:51","modified_gmt":"2023-09-05T11:15:51","slug":"merge-sort","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/merge-sort\/","title":{"rendered":"S\u0131ralamay\u0131 birle\u015ftir"},"content":{"rendered":"

Birle\u015ftirme s\u0131ralamas\u0131, bilgisayar bilimlerinde en etkili ve yayg\u0131n olarak kullan\u0131lan s\u0131ralama algoritmalar\u0131ndan biridir. Sorunun daha k\u00fc\u00e7\u00fck alt problemlere b\u00f6l\u00fcnd\u00fc\u011f\u00fc, yinelemeli olarak \u00e7\u00f6z\u00fcld\u00fc\u011f\u00fc ve daha sonra nihai sonucu elde etmek i\u00e7in birle\u015ftirildi\u011fi b\u00f6l ve y\u00f6net algoritmalar\u0131 kategorisine aittir. Kararl\u0131 ve \u00f6ng\u00f6r\u00fclebilir performans\u0131yla bilinen birle\u015ftirme s\u0131ralamas\u0131, b\u00fcy\u00fck veri k\u00fcmelerini s\u0131ralamada \u00e7e\u015fitli uygulamalar bulmu\u015f ve bu da onu hem geli\u015ftiriciler hem de veri analistleri i\u00e7in \u00f6nemli bir ara\u00e7 haline getirmi\u015ftir.<\/p>\n

Birle\u015ftirme s\u0131ralamas\u0131n\u0131n k\u00f6keninin tarihi ve bundan ilk s\u00f6z<\/h2>\n

Birle\u015ftirme s\u0131ralamas\u0131 kavram\u0131n\u0131n ge\u00e7mi\u015fi 1940'lara kadar uzan\u0131r ve ilk olarak 1945'te John von Neumann taraf\u0131ndan \u00f6nerilmi\u015ftir. Ancak, John von Neumann ve Stanislaw Ulam'\u0131n algoritmay\u0131 resmile\u015ftirip temel ilkelerini olu\u015fturmas\u0131 1948 y\u0131l\u0131na kadar de\u011fildi. Birle\u015ftirme s\u0131ralamas\u0131 \u00fczerindeki \u00e7al\u0131\u015fmalar\u0131 \u00f6ncelikle b\u00fcy\u00fck veri k\u00fcmelerini verimli bir \u015fekilde s\u0131ralamakla ilgiliydi ve bilgisayar bilimi ve algoritma tasar\u0131m\u0131nda gelecekteki geli\u015fmelerin temelini atmada \u00e7ok \u00f6nemli bir rol oynad\u0131.<\/p>\n

Birle\u015ftirme s\u0131ralamas\u0131 hakk\u0131nda ayr\u0131nt\u0131l\u0131 bilgi: Birle\u015ftirme s\u0131ralamas\u0131 konusunu geni\u015fletme<\/h2>\n

Birle\u015ftirme s\u0131ralamas\u0131, s\u0131ralanmam\u0131\u015f listeyi daha k\u00fc\u00e7\u00fck alt listelere b\u00f6lme, bu alt listeleri s\u0131ralama ve daha sonra bunlar\u0131 tamamen s\u0131ralanm\u0131\u015f bir liste elde etmek i\u00e7in yeniden birle\u015ftirme ilkesiyle \u00e7al\u0131\u015f\u0131r. S\u00fcre\u00e7 a\u015fa\u011f\u0131daki ad\u0131mlara ayr\u0131labilir:<\/p>\n

    \n
  1. \n

    B\u00f6lmek<\/strong>: S\u0131ralanmam\u0131\u015f liste, her bir alt liste tek bir \u00f6\u011fe i\u00e7erene kadar tekrar tekrar iki e\u015fit yar\u0131ya b\u00f6l\u00fcn\u00fcr.<\/p>\n<\/li>\n

  2. \n

    Fethetmek<\/strong>: Her bir \u00f6\u011fe, s\u0131ralanm\u0131\u015f bir alt liste olarak kabul edilir.<\/p>\n<\/li>\n

  3. \n

    Birle\u015ftirmek<\/strong>: S\u0131ralanan alt listeler daha sonra birle\u015ftirilir ve \u00f6\u011feler, son s\u0131ral\u0131 listeyi olu\u015fturacak \u015fekilde kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r ve birle\u015ftirilir.<\/p>\n<\/li>\n<\/ol>\n

    Birle\u015ftirme s\u0131ralamas\u0131, O(n log n) kadar bir zaman karma\u015f\u0131kl\u0131\u011f\u0131 sergiler; burada "n", listedeki \u00f6\u011felerin say\u0131s\u0131d\u0131r. Bu, Birle\u015ftirme s\u0131ralamas\u0131n\u0131, \u00f6zellikle b\u00fcy\u00fck veri k\u00fcmeleriyle u\u011fra\u015f\u0131rken Kabarc\u0131k s\u0131ralama ve Ekleme s\u0131ralama gibi yayg\u0131n olarak kullan\u0131lan di\u011fer s\u0131ralama algoritmalar\u0131ndan \u00f6nemli \u00f6l\u00e7\u00fcde daha h\u0131zl\u0131 hale getirir.<\/p>\n

    Birle\u015ftirme s\u0131ralamas\u0131n\u0131n i\u00e7 yap\u0131s\u0131: Birle\u015ftirme s\u0131ralamas\u0131 nas\u0131l \u00e7al\u0131\u015f\u0131r?<\/h2>\n

    Birle\u015ftirme s\u0131ralamas\u0131 \u00f6zyinelemeli bir yakla\u015f\u0131m kullan\u0131larak uygulan\u0131r. \u00c7ekirdek i\u015flev, girdi listesini iki yar\u0131ya b\u00f6ler ve her yar\u0131, ayn\u0131 \u00f6zyinelemeli yakla\u015f\u0131m kullan\u0131larak ba\u011f\u0131ms\u0131z olarak s\u0131ralan\u0131r. Bireysel yar\u0131mlar s\u0131raland\u0131ktan sonra birle\u015ftirme ad\u0131m\u0131 bunlar\u0131 tek bir s\u0131ral\u0131 listede birle\u015ftirir. Birle\u015ftirme i\u015flemi, her iki yar\u0131daki \u00f6\u011feleri kar\u015f\u0131la\u015ft\u0131ran ve bunlar\u0131 nihai \u00e7\u0131kt\u0131da birle\u015ftiren iki ana i\u015faret\u00e7iyle kolayla\u015ft\u0131r\u0131l\u0131r.<\/p>\n

    Birle\u015ftirme s\u0131ralamas\u0131n\u0131n temel \u00f6zelliklerinin analizi<\/h2>\n

    Birle\u015ftirme s\u0131ralamas\u0131, onu s\u0131ralama g\u00f6revleri i\u00e7in pop\u00fcler bir se\u00e7im haline getiren \u00e7e\u015fitli temel \u00f6zellikler sunar:<\/p>\n

      \n
    1. \n

      istikrar<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131 istikrarl\u0131 bir s\u0131ralama algoritmas\u0131d\u0131r; bu, e\u015fit \u00f6\u011felerin s\u0131ralanm\u0131\u015f \u00e7\u0131kt\u0131da orijinal s\u0131ralanmam\u0131\u015f listede oldu\u011fu gibi g\u00f6receli s\u0131ralar\u0131n\u0131 korudu\u011fu anlam\u0131na gelir.<\/p>\n<\/li>\n

    2. \n

      Tahmin edilebilir performans<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131n\u0131n O(n log n) zaman karma\u015f\u0131kl\u0131\u011f\u0131, tutarl\u0131 ve verimli performans sa\u011flayarak onu b\u00fcy\u00fck veri k\u00fcmeleri i\u00e7in uygun hale getirir.<\/p>\n<\/li>\n

    3. \n

      Ba\u011flant\u0131l\u0131 listeler i\u00e7in uygundur<\/strong>: Di\u011fer baz\u0131 s\u0131ralama algoritmalar\u0131ndan farkl\u0131 olarak Birle\u015ftirme s\u0131ralamas\u0131, rastgele eri\u015fim y\u00fck\u00fcn\u00fc en aza indiren s\u0131ral\u0131 eri\u015fim modeli nedeniyle ba\u011flant\u0131l\u0131 listelerde e\u015fit derecede iyi performans g\u00f6sterir.<\/p>\n<\/li>\n

    4. \n

      Uygulamas\u0131 kolay<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131n\u0131n \u00f6zyinelemeli yap\u0131s\u0131 ve basit birle\u015ftirme s\u00fcreci, \u00e7e\u015fitli programlama dillerinde uygulanmas\u0131n\u0131 nispeten kolayla\u015ft\u0131r\u0131r.<\/p>\n<\/li>\n<\/ol>\n

      Birle\u015ftirme s\u0131ralama t\u00fcrleri<\/h2>\n

      Birle\u015ftirme s\u0131ralamas\u0131n\u0131n iki ana \u00e7e\u015fidi vard\u0131r:<\/p>\n

        \n
      1. \n

        Yukar\u0131dan A\u015fa\u011f\u0131ya Birle\u015ftirme s\u0131ralamas\u0131<\/strong>: Bu, listeyi b\u00f6lmek ve alt listeleri s\u0131ralamak i\u00e7in \u00f6zyinelemeyi kullanan Birle\u015ftirme s\u0131ralamas\u0131n\u0131n klasik uygulamas\u0131d\u0131r. T\u00fcm listeyle ba\u015flar ve temel duruma (tek \u00f6\u011feli listeler) ula\u015f\u0131lana kadar onu yinelemeli olarak daha k\u00fc\u00e7\u00fck alt listelere b\u00f6ler. Alt listeler daha sonra s\u0131ralanm\u0131\u015f bir liste halinde birle\u015ftirilir.<\/p>\n<\/li>\n

      2. \n

        A\u015fa\u011f\u0131dan Yukar\u0131ya Birle\u015ftirme s\u0131ralamas\u0131<\/strong>: Bu varyantta algoritma, listeyi yinelemeli olarak sabit boyuttaki alt listelere b\u00f6ler ve bunlar\u0131 a\u015fa\u011f\u0131dan yukar\u0131ya do\u011fru birle\u015ftirir. \u0130\u015flem listenin tamam\u0131 s\u0131ralan\u0131ncaya kadar devam eder.<\/p>\n<\/li>\n<\/ol>\n

        Bir tabloda iki Birle\u015ftirme s\u0131ralamas\u0131 t\u00fcr\u00fcn\u00fc kar\u015f\u0131la\u015ft\u0131ral\u0131m:<\/p>\n\n\n\n\n\n\n
        Birle\u015ftir S\u0131rala De\u011fi\u015fkeni<\/th>\nArt\u0131lar\u0131<\/th>\nEksileri<\/th>\n<\/tr>\n<\/thead>\n
        Yukar\u0131dan A\u015fa\u011f\u0131ya Birle\u015ftirme s\u0131ralamas\u0131<\/td>\nAnla\u015f\u0131lmas\u0131 ve uygulanmas\u0131 daha kolay<\/td>\n\u00d6zyineleme i\u00e7in ek bellek gerektirir<\/td>\n<\/tr>\n
        A\u015fa\u011f\u0131dan Yukar\u0131ya Birle\u015ftirme s\u0131ralamas\u0131<\/td>\n\u00d6zyineleme yok, haf\u0131zadan tasarruf sa\u011flar<\/td>\nUygulamas\u0131 daha karma\u015f\u0131k<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Birle\u015ftirme s\u0131ralamas\u0131n\u0131 kullanma yollar\u0131, sorunlar ve kullan\u0131mla ilgili \u00e7\u00f6z\u00fcmleri<\/h2>\n

        Birle\u015ftirme s\u0131ralaman\u0131n verimlili\u011fi ve kararl\u0131l\u0131\u011f\u0131, \u00f6zellikle e\u015fit \u00f6\u011felerin s\u0131ras\u0131n\u0131n korunmas\u0131n\u0131n \u00e7ok \u00f6nemli oldu\u011fu durumlarda, onu b\u00fcy\u00fck veri k\u00fcmelerini s\u0131ralamak i\u00e7in ideal bir se\u00e7im haline getirir. Ancak kullan\u0131m\u0131yla ilgili birka\u00e7 zorluk ve potansiyel \u00e7\u00f6z\u00fcm vard\u0131r:<\/p>\n

          \n
        1. \n

          Bellek t\u00fcketimi<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131, \u00f6zellikle kapsaml\u0131 veri k\u00fcmeleriyle u\u011fra\u015f\u0131rken yinelenen \u00e7a\u011fr\u0131lar i\u00e7in ek bellek gerektirebilir. Bu durum, yinelemeyi \u00f6nleyen A\u015fa\u011f\u0131dan Yukar\u0131ya Birle\u015ftirme s\u0131ralama \u00e7e\u015fidi kullan\u0131larak azalt\u0131labilir.<\/p>\n<\/li>\n

        2. \n

          Performans ek y\u00fck\u00fc<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131n\u0131n da di\u011fer s\u0131ralama algoritmalar\u0131 gibi zaman karma\u015f\u0131kl\u0131\u011f\u0131 vard\u0131r. \u00c7o\u011fu senaryo i\u00e7in iyi performans g\u00f6sterse de geli\u015ftiriciler, ek y\u00fck\u00fc azaltmak amac\u0131yla daha k\u00fc\u00e7\u00fck veri k\u00fcmeleri i\u00e7in alternatif s\u0131ralama algoritmalar\u0131n\u0131 de\u011ferlendirebilir.<\/p>\n<\/li>\n

        3. \n

          \u00d6zel durumlar i\u00e7in optimizasyon<\/strong>: Birle\u015ftirme s\u0131ralamas\u0131n\u0131n zaman karma\u015f\u0131kl\u0131\u011f\u0131, veri da\u011f\u0131t\u0131m\u0131ndan ba\u011f\u0131ms\u0131z olarak tutarl\u0131 kal\u0131r. Halihaz\u0131rda k\u0131smen s\u0131ralanm\u0131\u015f veri k\u00fcmeleri i\u00e7in, neredeyse s\u0131ralanm\u0131\u015f listelerde daha iyi performans g\u00f6steren Ekleme s\u0131ralamas\u0131 gibi di\u011fer algoritmalar\u0131n kullan\u0131lmas\u0131 faydal\u0131 olabilir.<\/p>\n<\/li>\n<\/ol>\n

          Ana \u00f6zellikler ve benzer terimlerle kar\u015f\u0131la\u015ft\u0131rmalar<\/h2>\n

          Birle\u015ftirilmi\u015f s\u0131ralamay\u0131 bir tabloda yayg\u0131n olarak kullan\u0131lan di\u011fer iki s\u0131ralama algoritmas\u0131yla (H\u0131zl\u0131 s\u0131ralama ve Y\u0131\u011f\u0131n s\u0131ralama) kar\u015f\u0131la\u015ft\u0131ral\u0131m:<\/p>\n\n\n\n\n\n\n\n
          Algoritma<\/th>\nZaman Karma\u015f\u0131kl\u0131\u011f\u0131<\/th>\nistikrar<\/th>\nUzay Karma\u015f\u0131kl\u0131\u011f\u0131<\/th>\nUygulama Karma\u015f\u0131kl\u0131\u011f\u0131<\/th>\n<\/tr>\n<\/thead>\n
          S\u0131ralamay\u0131 birle\u015ftir<\/td>\nO(n log n)<\/td>\nStabil<\/td>\nA\u00e7\u0131k)<\/td>\nIl\u0131man<\/td>\n<\/tr>\n
          H\u0131zl\u0131 s\u0131ralama<\/td>\nO(n log n) (ortalama)<\/td>\nDengesiz<\/td>\nO(log n)<\/td>\nIl\u0131man<\/td>\n<\/tr>\n
          Y\u0131\u011f\u0131n s\u0131ralama<\/td>\nO(n log n)<\/td>\nDengesiz<\/td>\n\u00c7(1)<\/td>\nKarma\u015f\u0131k<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

          Birle\u015ftirme s\u0131ralamas\u0131yla ilgili gelece\u011fin perspektifleri ve teknolojileri<\/h2>\n

          Birle\u015ftirme s\u0131ralamas\u0131 temel bir s\u0131ralama algoritmas\u0131 olmaya devam ederken, s\u00fcrekli geli\u015fen bilgisayar bilimi alan\u0131, s\u0131ralama algoritmalar\u0131 i\u00e7in s\u00fcrekli olarak yeni perspektifler ve optimizasyonlar sunmaktad\u0131r. Ara\u015ft\u0131rmac\u0131lar ve geli\u015ftiriciler, paralel hesaplama, da\u011f\u0131t\u0131lm\u0131\u015f sistemler ve geli\u015fmi\u015f donan\u0131m mimarilerinden yararlanmak i\u00e7in Birle\u015ftirme s\u0131ralamas\u0131 ve di\u011fer s\u0131ralama algoritmalar\u0131n\u0131 uyarlaman\u0131n yollar\u0131n\u0131 s\u00fcrekli olarak ara\u015ft\u0131r\u0131yorlar. Bu aray\u0131\u015f, s\u0131ralama algoritmalar\u0131n\u0131n verimlili\u011fini ve \u00f6l\u00e7eklenebilirli\u011fini daha da geli\u015ftirmeyi ve onlar\u0131 b\u00fcy\u00fck veri ve ger\u00e7ek zamanl\u0131 i\u015fleme senaryolar\u0131na daha da uygulanabilir hale getirmeyi ama\u00e7l\u0131yor.<\/p>\n

          Proxy sunucular\u0131 nas\u0131l kullan\u0131labilir veya Birle\u015ftirme s\u0131ralamas\u0131yla nas\u0131l ili\u015fkilendirilebilir?<\/h2>\n

          OneProxy taraf\u0131ndan sa\u011flananlar gibi proxy sunucular\u0131, kullan\u0131c\u0131lar i\u00e7in internet trafi\u011finin y\u00f6netilmesinde ve optimize edilmesinde kritik bir rol oynar. Birle\u015ftirme s\u0131ralamas\u0131n\u0131n proxy sunucularla do\u011frudan bir ili\u015fkisi olmasa da, verimli veri i\u015flemenin \u00f6nemi internetteki h\u0131zl\u0131 ve kesintisiz veri aktar\u0131m\u0131 ihtiyac\u0131yla \u00f6rt\u00fc\u015fmektedir. Proxy sunucular, Birle\u015ftirme s\u0131ralamas\u0131n\u0131n kararl\u0131l\u0131\u011f\u0131 ve \u00f6ng\u00f6r\u00fclebilir performans \u00f6zelliklerinden yararlanarak veri y\u00f6netimi s\u00fcre\u00e7lerini iyile\u015ftirerek kullan\u0131c\u0131lar\u0131na sorunsuz tarama deneyimleri sa\u011flayabilir.<\/p>\n

          \u0130lgili Ba\u011flant\u0131lar<\/h2>\n

          Birle\u015ftirme s\u0131ralamas\u0131 hakk\u0131nda daha fazla bilgi i\u00e7in a\u015fa\u011f\u0131daki kaynaklara ba\u015fvurabilirsiniz:<\/p>\n

            \n
          1. GeeksforGeeks: Birle\u015ftir S\u0131rala<\/a><\/li>\n
          2. Vikipedi: Birle\u015ftir S\u0131rala<\/a><\/li>\n
          3. TopCoder: Birle\u015ftirme S\u0131ralama E\u011fitimi<\/a><\/li>\n<\/ol>\n

            Sonu\u00e7 olarak Birle\u015ftirme s\u0131ralamas\u0131, bilgisayar bilimindeki en g\u00fcvenilir ve verimli s\u0131ralama algoritmalar\u0131ndan biri olarak duruyor. B\u00f6l ve y\u00f6net yakla\u015f\u0131m\u0131, kararl\u0131l\u0131\u011f\u0131 ve \u00f6ng\u00f6r\u00fclebilir performans\u0131, onu b\u00fcy\u00fck veri k\u00fcmelerini s\u0131ralamak i\u00e7in tercih edilen bir se\u00e7im haline getiriyor. Teknoloji geli\u015fmeye devam ettik\u00e7e Birle\u015ftirme s\u0131ralamas\u0131, \u00e7e\u015fitli uygulama ve sistemlerin d\u00fczg\u00fcn i\u015fleyi\u015fine s\u00fcrekli olarak katk\u0131da bulunarak, ay\u0131rma \u00e7\u00f6z\u00fcmlerinde \u00f6nemli bir bile\u015fen olmaya devam edecektir.<\/p>","protected":false},"featured_media":468892,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477994","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Merge Sort: A Comprehensive Guide<\/mark>","faq_items":[{"question":"What is Merge sort and why is it important?","answer":"

            Merge sort is a widely-used sorting algorithm in computer science. It efficiently sorts large datasets by dividing the list into smaller sublists, sorting them, and then merging them back to obtain a fully sorted list. Its importance lies in its stable and predictable performance, making it a crucial tool for developers and data analysts dealing with extensive data.<\/p>"},{"question":"Who proposed Merge sort, and when was it first mentioned?","answer":"

            Merge sort was first proposed by John von Neumann in 1945, but it was formalized and established by John von Neumann and Stanislaw Ulam in 1948. Their work on Merge sort laid the foundation for future developments in algorithm design and computer science.<\/p>"},{"question":"How does Merge sort work internally?","answer":"

            Merge sort works on a divide-and-conquer approach. It recursively divides the unsorted list into two halves, sorts them independently, and then merges them back into a fully sorted list. The merging process uses two pointers to compare and combine elements.<\/p>"},{"question":"What are the key features of Merge sort?","answer":"

            Merge sort offers stability, meaning that equal elements retain their original order in the sorted output. It demonstrates predictable performance with a time complexity of O(n log n), making it faster than many other sorting algorithms. Moreover, Merge sort is suitable for linked lists and relatively easy to implement.<\/p>"},{"question":"What are the different types of Merge sort?","answer":"

            There are two main variants of Merge sort: Top-Down Merge sort and Bottom-Up Merge sort. The former uses recursion to divide and sort the list, while the latter iteratively divides the list into fixed-size sublists and merges them in a bottom-up fashion.<\/p>"},{"question":"How can Merge sort be used effectively, and what problems may arise?","answer":"

            Merge sort is ideal for sorting large datasets while preserving the order of equal elements. However, it may consume additional memory for recursion, which can be mitigated by using the Bottom-Up Merge sort variant. Additionally, for partially sorted data, considering alternative algorithms like Insertion sort may optimize performance.<\/p>"},{"question":"How does Merge sort compare with other sorting algorithms?","answer":"

            In comparison to Quick sort and Heap sort, Merge sort stands out with its stability and moderate implementation complexity. Quick sort has similar average time complexity, but it is unstable and has a different space complexity. On the other hand, Heap sort is also unstable but has a constant space complexity, making it more complex to implement.<\/p>"},{"question":"What does the future hold for Merge sort and related technologies?","answer":"

            As technology evolves, researchers and developers continue to explore ways to adapt sorting algorithms like Merge sort to leverage parallel computing, distributed systems, and advanced hardware architectures. These advancements aim to further enhance efficiency and scalability, enabling sorting algorithms to handle big data and real-time processing scenarios effectively.<\/p>"},{"question":"How are proxy servers associated with Merge sort?","answer":"

            While Merge sort itself may not have a direct association with proxy servers, the efficient data handling principles align with the need for rapid and seamless data transfer on the internet. Proxy servers, such as OneProxy, can leverage Merge sort's stable performance characteristics to enhance their data management processes, ensuring a smooth browsing experience for users.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/477994","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/477994\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/468892"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=477994"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}