{"id":478928,"date":"2023-08-09T09:40:29","date_gmt":"2023-08-09T09:40:29","guid":{"rendered":""},"modified":"2023-09-05T11:17:49","modified_gmt":"2023-09-05T11:17:49","slug":"sequence-transduction","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/sequence-transduction\/","title":{"rendered":"S\u1ef1 t\u1ea3i n\u1ea1p tr\u00ecnh t\u1ef1"},"content":{"rendered":"<p>Chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1 l\u00e0 m\u1ed9t qu\u00e1 tr\u00ecnh bi\u1ebfn \u0111\u1ed5i tr\u00ecnh t\u1ef1 n\u00e0y th\u00e0nh tr\u00ecnh t\u1ef1 kh\u00e1c, trong \u0111\u00f3 tr\u00ecnh t\u1ef1 \u0111\u1ea7u v\u00e0o v\u00e0 \u0111\u1ea7u ra c\u00f3 th\u1ec3 kh\u00e1c nhau v\u1ec1 \u0111\u1ed9 d\u00e0i. N\u00f3 th\u01b0\u1eddng \u0111\u01b0\u1ee3c t\u00ecm th\u1ea5y trong c\u00e1c \u1ee9ng d\u1ee5ng kh\u00e1c nhau nh\u01b0 nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i, d\u1ecbch m\u00e1y v\u00e0 x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean (NLP).<\/p>\n<h2>L\u1ecbch s\u1eed ngu\u1ed3n g\u1ed1c c\u1ee7a s\u1ef1 truy\u1ec1n tr\u00ecnh t\u1ef1 v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>Chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1 nh\u01b0 m\u1ed9t kh\u00e1i ni\u1ec7m c\u00f3 ngu\u1ed3n g\u1ed1c t\u1eeb gi\u1eefa th\u1ebf k\u1ef7 20, v\u1edbi nh\u1eefng ph\u00e1t tri\u1ec3n ban \u0111\u1ea7u trong d\u1ecbch m\u00e1y th\u1ed1ng k\u00ea v\u00e0 nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i. V\u1ea5n \u0111\u1ec1 chuy\u1ec3n \u0111\u1ed5i chu\u1ed7i n\u00e0y th\u00e0nh chu\u1ed7i kh\u00e1c l\u1ea7n \u0111\u1ea7u ti\u00ean \u0111\u01b0\u1ee3c nghi\u00ean c\u1ee9u nghi\u00eam ng\u1eb7t trong c\u00e1c l\u0129nh v\u1ef1c n\u00e0y. Theo th\u1eddi gian, nhi\u1ec1u m\u00f4 h\u00ecnh v\u00e0 ph\u01b0\u01a1ng ph\u00e1p kh\u00e1c nhau \u0111\u00e3 \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n \u0111\u1ec3 l\u00e0m cho vi\u1ec7c chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1 tr\u1edf n\u00ean hi\u1ec7u qu\u1ea3 v\u00e0 ch\u00ednh x\u00e1c h\u01a1n.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 Chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1: M\u1edf r\u1ed9ng Chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1 ch\u1ee7 \u0111\u1ec1<\/h2>\n<p>Vi\u1ec7c truy\u1ec1n tr\u00ecnh t\u1ef1 c\u00f3 th\u1ec3 \u0111\u1ea1t \u0111\u01b0\u1ee3c th\u00f4ng qua c\u00e1c m\u00f4 h\u00ecnh v\u00e0 thu\u1eadt to\u00e1n kh\u00e1c nhau. C\u00e1c ph\u01b0\u01a1ng ph\u00e1p ban \u0111\u1ea7u bao g\u1ed3m c\u00e1c m\u00f4 h\u00ecnh Markov \u1ea9n (HMM) v\u00e0 c\u00e1c b\u1ed9 chuy\u1ec3n \u0111\u1ed5i tr\u1ea1ng th\u00e1i h\u1eefu h\u1ea1n. Nh\u1eefng ph\u00e1t tri\u1ec3n g\u1ea7n \u0111\u00e2y h\u01a1n \u0111\u00e3 ch\u1ee9ng ki\u1ebfn s\u1ef1 gia t\u0103ng c\u1ee7a m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh, \u0111\u1eb7c bi\u1ec7t l\u00e0 m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh t\u00e1i ph\u00e1t (RNN) v\u00e0 c\u00e1c m\u00e1y bi\u1ebfn \u00e1p s\u1eed d\u1ee5ng c\u01a1 ch\u1ebf ch\u00fa \u00fd.<\/p>\n<h3>M\u00f4 h\u00ecnh v\u00e0 thu\u1eadt to\u00e1n<\/h3>\n<ol>\n<li><strong>M\u00f4 h\u00ecnh Markov \u1ea9n (HMM)<\/strong>: C\u00e1c m\u00f4 h\u00ecnh th\u1ed1ng k\u00ea gi\u1ea3 \u0111\u1ecbnh m\u1ed9t chu\u1ed7i tr\u1ea1ng th\u00e1i &#039;\u1ea9n&#039;.<\/li>\n<li><strong>B\u1ed9 chuy\u1ec3n \u0111\u1ed5i tr\u1ea1ng th\u00e1i h\u1eefu h\u1ea1n (FST)<\/strong>: S\u1eed d\u1ee5ng c\u00e1c chuy\u1ec3n \u0111\u1ed5i tr\u1ea1ng th\u00e1i \u0111\u1ec3 chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1.<\/li>\n<li><strong>M\u1ea1ng th\u1ea7n kinh t\u00e1i ph\u00e1t (RNN)<\/strong>: M\u1ea1ng th\u1ea7n kinh c\u00f3 v\u00f2ng l\u1eb7p \u0111\u1ec3 cho ph\u00e9p l\u01b0u gi\u1eef th\u00f4ng tin.<\/li>\n<li><strong>M\u00e1y bi\u1ebfn \u00e1p<\/strong>: C\u00e1c m\u00f4 h\u00ecnh d\u1ef1a tr\u00ean s\u1ef1 ch\u00fa \u00fd n\u1eafm b\u1eaft \u0111\u01b0\u1ee3c s\u1ef1 ph\u1ee5 thu\u1ed9c t\u1ed5ng th\u1ec3 trong chu\u1ed7i \u0111\u1ea7u v\u00e0o.<\/li>\n<\/ol>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a qu\u00e1 tr\u00ecnh truy\u1ec1n tr\u00ecnh t\u1ef1: Qu\u00e1 tr\u00ecnh truy\u1ec1n tr\u00ecnh t\u1ef1 ho\u1ea1t \u0111\u1ed9ng nh\u01b0 th\u1ebf n\u00e0o<\/h2>\n<p>Qu\u00e1 tr\u00ecnh truy\u1ec1n tr\u00ecnh t\u1ef1 th\u01b0\u1eddng bao g\u1ed3m c\u00e1c b\u01b0\u1edbc sau:<\/p>\n<ol>\n<li><strong>M\u00e3 th\u00f4ng b\u00e1o<\/strong>: Chu\u1ed7i \u0111\u1ea7u v\u00e0o \u0111\u01b0\u1ee3c chia th\u00e0nh c\u00e1c \u0111\u01a1n v\u1ecb ho\u1eb7c m\u00e3 th\u00f4ng b\u00e1o nh\u1ecf h\u01a1n.<\/li>\n<li><strong>M\u00e3 h\u00f3a<\/strong>: C\u00e1c m\u00e3 th\u00f4ng b\u00e1o sau \u0111\u00f3 \u0111\u01b0\u1ee3c bi\u1ec3u di\u1ec5n d\u01b0\u1edbi d\u1ea1ng vect\u01a1 s\u1ed1 b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng b\u1ed9 m\u00e3 h\u00f3a.<\/li>\n<li><strong>Chuy\u1ec3n \u0111\u1ed5i<\/strong>: Sau \u0111\u00f3, m\u00f4 h\u00ecnh t\u1ea3i n\u1ea1p s\u1ebd chuy\u1ec3n \u0111\u1ed5i chu\u1ed7i \u0111\u1ea7u v\u00e0o \u0111\u01b0\u1ee3c m\u00e3 h\u00f3a th\u00e0nh m\u1ed9t chu\u1ed7i kh\u00e1c, th\u01b0\u1eddng th\u00f4ng qua nhi\u1ec1u l\u1edbp t\u00ednh to\u00e1n.<\/li>\n<li><strong>Gi\u1ea3i m\u00e3<\/strong>: Chu\u1ed7i \u0111\u00e3 chuy\u1ec3n \u0111\u1ed5i \u0111\u01b0\u1ee3c gi\u1ea3i m\u00e3 th\u00e0nh \u0111\u1ecbnh d\u1ea1ng \u0111\u1ea7u ra mong mu\u1ed1n.<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a truy\u1ec1n t\u1ea3i tr\u00ecnh t\u1ef1<\/h2>\n<ul>\n<li><strong>Uy\u1ec3n chuy\u1ec3n<\/strong>: C\u00f3 th\u1ec3 x\u1eed l\u00fd c\u00e1c chu\u1ed7i c\u00f3 \u0111\u1ed9 d\u00e0i kh\u00e1c nhau.<\/li>\n<li><strong>\u0110\u1ed9 ph\u1ee9c t\u1ea1p<\/strong>: C\u00e1c m\u00f4 h\u00ecnh c\u00f3 th\u1ec3 \u0111\u00f2i h\u1ecfi t\u00ednh to\u00e1n chuy\u00ean s\u00e2u.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng th\u00edch \u1ee9ng<\/strong>: C\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c \u0111i\u1ec1u ch\u1ec9nh cho ph\u00f9 h\u1ee3p v\u1edbi c\u00e1c t\u00e1c v\u1ee5 c\u1ee5 th\u1ec3 nh\u01b0 d\u1ecbch thu\u1eadt ho\u1eb7c nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i.<\/li>\n<li><strong>S\u1ef1 ph\u1ee5 thu\u1ed9c v\u00e0o d\u1eef li\u1ec7u<\/strong>: Ch\u1ea5t l\u01b0\u1ee3ng truy\u1ec1n t\u1ea3i th\u01b0\u1eddng ph\u1ee5 thu\u1ed9c v\u00e0o s\u1ed1 l\u01b0\u1ee3ng v\u00e0 ch\u1ea5t l\u01b0\u1ee3ng d\u1eef li\u1ec7u hu\u1ea5n luy\u1ec7n.<\/li>\n<\/ul>\n<h2>C\u00e1c lo\u1ea1i truy\u1ec1n tr\u00ecnh t\u1ef1<\/h2>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>S\u1ef1 mi\u00eau t\u1ea3<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>D\u1ecbch m\u00e1y<\/td>\n<td>D\u1ecbch v\u0103n b\u1ea3n t\u1eeb ng\u00f4n ng\u1eef n\u00e0y sang ng\u00f4n ng\u1eef kh\u00e1c<\/td>\n<\/tr>\n<tr>\n<td>Nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i<\/td>\n<td>D\u1ecbch ng\u00f4n ng\u1eef n\u00f3i th\u00e0nh v\u0103n b\u1ea3n vi\u1ebft<\/td>\n<\/tr>\n<tr>\n<td>Ch\u00fa th\u00edch h\u00ecnh \u1ea3nh<\/td>\n<td>M\u00f4 t\u1ea3 h\u00ecnh \u1ea3nh b\u1eb1ng ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean<\/td>\n<\/tr>\n<tr>\n<td>G\u1eafn th\u1ebb m\u1ed9t ph\u1ea7n c\u1ee7a b\u00e0i ph\u00e1t bi\u1ec3u<\/td>\n<td>G\u00e1n c\u00e1c ph\u1ea7n c\u1ee7a l\u1eddi n\u00f3i cho c\u00e1c t\u1eeb ri\u00eang l\u1ebb trong v\u0103n b\u1ea3n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng Truy\u1ec1n tr\u00ecnh t\u1ef1, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng<\/h2>\n<ul>\n<li><strong>C\u00f4ng d\u1ee5ng<\/strong>: Trong tr\u1ee3 l\u00fd gi\u1ecdng n\u00f3i, d\u1ecbch thu\u1eadt th\u1eddi gian th\u1ef1c, v.v.<\/li>\n<li><strong>C\u00e1c v\u1ea5n \u0111\u1ec1<\/strong>: Trang b\u1ecb qu\u00e1 m\u1ee9c, y\u00eau c\u1ea7u d\u1eef li\u1ec7u hu\u1ea5n luy\u1ec7n m\u1edf r\u1ed9ng, t\u00e0i nguy\u00ean t\u00ednh to\u00e1n.<\/li>\n<li><strong>C\u00e1c gi\u1ea3i ph\u00e1p<\/strong>: K\u1ef9 thu\u1eadt ch\u00ednh quy h\u00f3a, h\u1ecdc chuy\u1ec3n giao, t\u1ed1i \u01b0u h\u00f3a t\u00e0i nguy\u00ean t\u00ednh to\u00e1n.<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 nh\u1eefng so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1<\/h2>\n<ul>\n<li><strong>Chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1 so v\u1edbi s\u1eafp x\u1ebfp tr\u00ecnh t\u1ef1<\/strong>: Trong khi c\u0103n ch\u1ec9nh nh\u1eb1m m\u1ee5c \u0111\u00edch t\u00ecm ra s\u1ef1 t\u01b0\u01a1ng \u1ee9ng gi\u1eefa c\u00e1c ph\u1ea7n t\u1eed trong hai chu\u1ed7i, th\u00ec s\u1ef1 chuy\u1ec3n \u0111\u1ed5i nh\u1eb1m m\u1ee5c \u0111\u00edch chuy\u1ec3n \u0111\u1ed5i chu\u1ed7i n\u00e0y th\u00e0nh chu\u1ed7i kh\u00e1c.<\/li>\n<li><strong>Truy\u1ec1n tr\u00ecnh t\u1ef1 so v\u1edbi t\u1ea1o tr\u00ecnh t\u1ef1<\/strong>: Qu\u00e1 tr\u00ecnh truy\u1ec1n t\u1ea3i l\u1ea5y m\u1ed9t chu\u1ed7i \u0111\u1ea7u v\u00e0o \u0111\u1ec3 t\u1ea1o ra m\u1ed9t chu\u1ed7i \u0111\u1ea7u ra, trong khi vi\u1ec7c t\u1ea1o ra c\u00f3 th\u1ec3 kh\u00f4ng y\u00eau c\u1ea7u m\u1ed9t chu\u1ed7i \u0111\u1ea7u v\u00e0o.<\/li>\n<\/ul>\n<h2>Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn truy\u1ec1n tr\u00ecnh t\u1ef1<\/h2>\n<p>Nh\u1eefng ti\u1ebfn b\u1ed9 trong c\u00f4ng ngh\u1ec7 ph\u1ea7n c\u1ee9ng v\u00e0 h\u1ecdc s\u00e2u \u0111\u01b0\u1ee3c k\u1ef3 v\u1ecdng s\u1ebd n\u00e2ng cao h\u01a1n n\u1eefa kh\u1ea3 n\u0103ng truy\u1ec1n t\u1ea3i chu\u1ed7i. Nh\u1eefng \u0111\u1ed5i m\u1edbi trong h\u1ecdc t\u1eadp kh\u00f4ng gi\u00e1m s\u00e1t, t\u00ednh to\u00e1n ti\u1ebft ki\u1ec7m n\u0103ng l\u01b0\u1ee3ng v\u00e0 x\u1eed l\u00fd th\u1eddi gian th\u1ef1c \u0111\u1ec1u l\u00e0 nh\u1eefng tri\u1ec3n v\u1ecdng trong t\u01b0\u01a1ng lai.<\/p>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi qu\u00e1 tr\u00ecnh truy\u1ec1n tr\u00ecnh t\u1ef1<\/h2>\n<p>M\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 t\u1ea1o \u0111i\u1ec1u ki\u1ec7n thu\u1eadn l\u1ee3i cho c\u00e1c nhi\u1ec7m v\u1ee5 truy\u1ec1n t\u1ea3i chu\u1ed7i b\u1eb1ng c\u00e1ch cung c\u1ea5p kh\u1ea3 n\u0103ng truy c\u1eadp d\u1eef li\u1ec7u t\u1ed1t h\u01a1n, \u0111\u1ea3m b\u1ea3o t\u00ednh \u1ea9n danh trong qu\u00e1 tr\u00ecnh thu th\u1eadp d\u1eef li\u1ec7u \u0111\u1ec3 \u0111\u00e0o t\u1ea1o v\u00e0 c\u00e2n b\u1eb1ng t\u1ea3i trong c\u00e1c nhi\u1ec7m v\u1ee5 truy\u1ec1n t\u1ea3i quy m\u00f4 l\u1edbn.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1409.3215\" target=\"_new\" rel=\"noopener nofollow\">H\u1ecdc Seq2Seq<\/a>: B\u00e0i vi\u1ebft chuy\u00ean \u0111\u1ec1 v\u1ec1 tr\u00ecnh t\u1ef1 h\u1ecdc t\u1eadp.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1706.03762\" target=\"_new\" rel=\"noopener nofollow\">M\u00f4 h\u00ecnh m\u00e1y bi\u1ebfn \u00e1p<\/a>: B\u00e0i vi\u1ebft m\u00f4 t\u1ea3 m\u00f4 h\u00ecnh m\u00e1y bi\u1ebfn \u00e1p.<\/li>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/document\/1162252\" target=\"_new\" rel=\"noopener nofollow\">T\u1ed5ng quan v\u1ec1 l\u1ecbch s\u1eed nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i<\/a>: T\u1ed5ng quan v\u1ec1 nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i n\u00eau b\u1eadt vai tr\u00f2 c\u1ee7a vi\u1ec7c chuy\u1ec3n \u0111\u1ed5i tr\u00ecnh t\u1ef1.<\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">OneProxy<\/a>: D\u00e0nh cho c\u00e1c gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn m\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong c\u00e1c t\u00e1c v\u1ee5 truy\u1ec1n t\u1ea3i chu\u1ed7i.<\/li>\n<\/ul>","protected":false},"featured_media":470467,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478928","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Sequence Transduction<\/mark>","faq_items":[{"question":"What is Sequence Transduction?","answer":"<p>Sequence transduction is a process that converts one sequence into another. It is commonly used in applications such as speech recognition, machine translation, and natural language processing (NLP). Different models like Hidden Markov Models, Finite-State Transducers, and neural networks like RNNs and transformers are employed for this purpose.<\/p>"},{"question":"What are the historical origins of Sequence Transduction?","answer":"<p>Sequence transduction originated in the mid-20th century, with early applications in statistical machine translation and speech recognition. The concept has evolved over time with various models and methods being developed for more efficient and accurate sequence transformations.<\/p>"},{"question":"How does Sequence Transduction work?","answer":"<p>Sequence transduction works by tokenizing the input sequence into smaller units, encoding these tokens as numerical vectors, transforming the encoded sequence into another sequence through a transduction model, and then decoding the transformed sequence into the desired output format.<\/p>"},{"question":"What are the key features of Sequence Transduction?","answer":"<p>The key features of sequence transduction include its flexibility in handling sequences of varying lengths, its complexity, adaptability to specific tasks, and dependence on the amount and quality of training data.<\/p>"},{"question":"What types of Sequence Transduction exist?","answer":"<p>Types of sequence transduction include Machine Translation, Speech Recognition, Image Captioning, and Part-of-Speech Tagging. These various types are used to translate text, recognize spoken language, describe images, and assign parts of speech to words.<\/p>"},{"question":"What are the common problems and solutions in using Sequence Transduction?","answer":"<p>Common problems in using sequence transduction include overfitting, the requirement of extensive training data, and computational resource constraints. Solutions include using regularization techniques, transfer learning, and optimizing computational resources.<\/p>"},{"question":"How are Sequence Transduction and Proxy Servers related?","answer":"<p>Proxy servers can be associated with sequence transduction by facilitating better accessibility to data, ensuring anonymity during data collection for training, and load balancing in large-scale transduction tasks.<\/p>"},{"question":"What are the future prospects of Sequence Transduction?","answer":"<p>Future prospects of sequence transduction include advancements in deep learning and hardware technologies, innovations in unsupervised learning, energy-efficient computation, and real-time processing. It is expected to further enhance capabilities in various applications.<\/p>"},{"question":"Where can I find more resources on Sequence Transduction?","answer":"<p>You can find more detailed information on Sequence Transduction in resources like the seminal paper on Seq2Seq Learning, the paper describing the transformer model, an overview of speech recognition highlighting sequence transduction's role, and through the website OneProxy for related proxy server solutions. Links to these resources are provided in the related links section of the article.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478928","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478928\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/470467"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478928"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}