{"id":478093,"date":"2023-08-09T09:27:19","date_gmt":"2023-08-09T09:27:19","guid":{"rendered":""},"modified":"2023-09-05T11:16:02","modified_gmt":"2023-09-05T11:16:02","slug":"named-entity-recognition-ner","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/named-entity-recognition-ner\/","title":{"rendered":"Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER)"},"content":{"rendered":"<p>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) hakk\u0131nda k\u0131sa bilgi: Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER), Do\u011fal Dil \u0130\u015fleme&#039;nin (NLP) metindeki adland\u0131r\u0131lm\u0131\u015f varl\u0131klar\u0131 tan\u0131mlamaya ve s\u0131n\u0131fland\u0131rmaya odaklanan bir alt alan\u0131d\u0131r. Adland\u0131r\u0131lm\u0131\u015f varl\u0131klar ki\u015filer, kurulu\u015flar, konumlar, zaman ifadeleri, miktarlar, parasal de\u011ferler, y\u00fczdeler ve daha fazlas\u0131 olabilir.<\/p>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131mas\u0131n\u0131n (NER) K\u00f6keni ve \u0130lk S\u00f6z\u00fc<\/h2>\n<p>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma 1990&#039;lar\u0131n ba\u015f\u0131nda \u015fekillenmeye ba\u015flad\u0131. NER&#039;in ilk \u00f6rneklerinden biri 1995&#039;teki Alt\u0131nc\u0131 Mesaj Anlama Konferans\u0131&#039;nda (MUC-6) ger\u00e7ekle\u015fti. Bu noktadan sonra, bilgisayarlar\u0131n insan dilini daha etkili bir \u015fekilde anlamas\u0131n\u0131 ve yorumlamas\u0131n\u0131 sa\u011flama ihtiyac\u0131n\u0131n etkisiyle bu alandaki ara\u015ft\u0131rmalar geli\u015fmeye ba\u015flad\u0131.<\/p>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) Hakk\u0131nda Detayl\u0131 Bilgi: Konuyu Geni\u015fletmek<\/h2>\n<p>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER), do\u011fal dillerin i\u015flenmesinde \u00e7e\u015fitli i\u015flevlere hizmet eder. Uygulamalar\u0131 bilgi eri\u015fimi, makine \u00e7evirisi ve veri madencili\u011fi gibi bir\u00e7ok alana yay\u0131lmaktad\u0131r. NER iki ana b\u00f6l\u00fcmden olu\u015fur:<\/p>\n<ol>\n<li><strong>Varl\u0131k Kimli\u011fi<\/strong>: Metindeki atomik \u00f6\u011felerin yerini ki\u015fi, kurulu\u015f, konum vb. gibi \u00f6nceden tan\u0131mlanm\u0131\u015f kategorilere ay\u0131rma ve s\u0131n\u0131fland\u0131rma.<\/li>\n<li><strong>Varl\u0131k S\u0131n\u0131fland\u0131rmas\u0131<\/strong>: Tan\u0131mlanan varl\u0131klar\u0131n \u00f6nceden tan\u0131mlanm\u0131\u015f \u00e7e\u015fitli s\u0131n\u0131flara s\u0131n\u0131fland\u0131r\u0131lmas\u0131.<\/li>\n<\/ol>\n<p>NER&#039;e kural tabanl\u0131 sistemler, denetimli \u00f6\u011frenme, yar\u0131 denetimli \u00f6\u011frenme ve denetimsiz \u00f6\u011frenme arac\u0131l\u0131\u011f\u0131yla yakla\u015f\u0131labilir.<\/p>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma&#039;n\u0131n (NER) \u0130\u00e7 Yap\u0131s\u0131: Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) Nas\u0131l \u00c7al\u0131\u015f\u0131r?<\/h2>\n<p>NER&#039;in i\u00e7 yap\u0131s\u0131 birka\u00e7 a\u015famadan olu\u015fur:<\/p>\n<ol>\n<li><strong>Tokenizasyon<\/strong>: Metni tek tek kelimelere veya simgelere ay\u0131rma.<\/li>\n<li><strong>Konu\u015fma K\u0131sm\u0131nda Etiketleme<\/strong>: Belirte\u00e7lerin gramer kategorilerinin belirlenmesi.<\/li>\n<li><strong>Ayr\u0131\u015ft\u0131rma<\/strong>: C\u00fcmlenin gramer yap\u0131s\u0131n\u0131 analiz etme.<\/li>\n<li><strong>Varl\u0131k Tan\u0131mlama ve S\u0131n\u0131fland\u0131rma<\/strong>: Varl\u0131klar\u0131n tan\u0131mlanmas\u0131 ve \u00f6nceden tan\u0131mlanm\u0131\u015f kategorilere g\u00f6re s\u0131n\u0131fland\u0131r\u0131lmas\u0131.<\/li>\n<\/ol>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma&#039;n\u0131n (NER) Temel \u00d6zelliklerinin Analizi<\/h2>\n<p>NER&#039;in temel \u00f6zellikleri \u015funlar\u0131 i\u00e7erir:<\/p>\n<ol>\n<li><strong>Kesinlik<\/strong>: Varl\u0131klar\u0131 do\u011fru bir \u015fekilde tan\u0131mlama ve s\u0131n\u0131fland\u0131rma yetene\u011fi.<\/li>\n<li><strong>H\u0131z<\/strong>: Metnin i\u015flenmesi i\u00e7in ge\u00e7en s\u00fcre.<\/li>\n<li><strong>\u00d6l\u00e7eklenebilirlik<\/strong>: B\u00fcy\u00fck veri k\u00fcmelerini i\u015fleyebilme yetene\u011fi.<\/li>\n<li><strong>Dil Ba\u011f\u0131ms\u0131zl\u0131\u011f\u0131<\/strong>: Farkl\u0131 dillerde kullan\u0131labilme yetene\u011fi.<\/li>\n<li><strong>Uyarlanabilirlik<\/strong>: Belirli alan adlar\u0131 veya sekt\u00f6rler i\u00e7in \u00f6zelle\u015ftirilebilir.<\/li>\n<\/ol>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) T\u00fcrleri: Tablolar\u0131 ve Listeleri Kullan\u0131n<\/h2>\n<p>NER t\u00fcrleri \u015fu \u015fekilde s\u0131n\u0131fland\u0131r\u0131labilir:<\/p>\n<table>\n<thead>\n<tr>\n<th>Tip<\/th>\n<th>Tan\u0131m<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Kural Tabanl\u0131 NER<\/td>\n<td>\u00d6nceden tan\u0131mlanm\u0131\u015f dilbilgisi kurallar\u0131n\u0131 kullan\u0131r<\/td>\n<\/tr>\n<tr>\n<td>Denetimli NER<\/td>\n<td>E\u011fitim modelleri i\u00e7in etiketli verileri kullan\u0131r<\/td>\n<\/tr>\n<tr>\n<td>Yar\u0131 Denetimli NER<\/td>\n<td>Etiketli ve etiketsiz verileri birle\u015ftirir<\/td>\n<\/tr>\n<tr>\n<td>Denetimsiz NER<\/td>\n<td>Etiketli veri gerektirmez<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma&#039;y\u0131 (NER) Kullanma Yollar\u0131, Sorunlar ve Kullan\u0131ma \u0130li\u015fkin \u00c7\u00f6z\u00fcmleri<\/h2>\n<p>NER&#039;i kullanma yollar\u0131 aras\u0131nda arama motorlar\u0131, m\u00fc\u015fteri deste\u011fi, sa\u011fl\u0131k hizmetleri ve daha fazlas\u0131 bulunur. Baz\u0131 sorunlar ve \u00e7\u00f6z\u00fcmleri \u015funlard\u0131r:<\/p>\n<ul>\n<li><strong>Sorun<\/strong>: Etiketli veri eksikli\u011fi.<br \/>\n<strong>\u00c7\u00f6z\u00fcm<\/strong>: Yar\u0131 denetimli veya denetimsiz \u00f6\u011frenmeyi kullan\u0131n.<\/li>\n<li><strong>Sorun<\/strong>: Dile \u00f6zg\u00fc k\u0131s\u0131tlamalar.<br \/>\n<strong>\u00c7\u00f6z\u00fcm<\/strong>: Modeli belirli bir dile veya alana uyarlay\u0131n.<\/li>\n<\/ul>\n<h2>Ana \u00d6zellikler ve Benzer Terimlerle Di\u011fer Kar\u015f\u0131la\u015ft\u0131rmalar<\/h2>\n<table>\n<thead>\n<tr>\n<th>\u00d6zellik<\/th>\n<th>NER<\/th>\n<th>Di\u011fer NLP G\u00f6revleri<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Odak<\/td>\n<td>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131klar<\/td>\n<td>Genel Metin<\/td>\n<\/tr>\n<tr>\n<td>Karma\u015f\u0131kl\u0131k<\/td>\n<td>Orta ila Y\u00fcksek<\/td>\n<td>De\u011fi\u015fir<\/td>\n<\/tr>\n<tr>\n<td>Ba\u015fvuru<\/td>\n<td>\u00d6zel<\/td>\n<td>Kal\u0131n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) ile \u0130lgili Gelece\u011fin Perspektifleri ve Teknolojileri<\/h2>\n<p>Gelecek perspektifleri aras\u0131nda NER&#039;in derin \u00f6\u011frenmeyle entegrasyonu, \u00e7e\u015fitli dillere daha fazla uyarlanabilirlik ve ger\u00e7ek zamanl\u0131 i\u015fleme yetenekleri yer al\u0131yor.<\/p>\n<h2>Proxy Sunucular\u0131 Nas\u0131l Kullan\u0131labilir veya Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma (NER) ile Nas\u0131l \u0130li\u015fkilendirilebilir?<\/h2>\n<p>OneProxy taraf\u0131ndan sa\u011flananlara benzer proxy sunucular, NER i\u00e7in veri toplamak amac\u0131yla kullan\u0131labilir. \u0130stekleri anonimle\u015ftirerek, NER modellerinin e\u011fitimi ve uygulanmas\u0131 i\u00e7in metin verilerinin verimli ve etik bir \u015fekilde toplanmas\u0131na olanak tan\u0131r.<\/p>\n<h2>\u0130lgili Ba\u011flant\u0131lar<\/h2>\n<ul>\n<li><a href=\"https:\/\/nlp.stanford.edu\/software\/CRF-NER.shtml\" target=\"_new\" rel=\"noopener nofollow\">Stanford NLP Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma Arac\u0131<\/a><\/li>\n<li><a href=\"https:\/\/www.nltk.org\/book\/ch07.html\" target=\"_new\" rel=\"noopener nofollow\">NLTK Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma<\/a><\/li>\n<li><a href=\"https:\/\/spacy.io\/usage\/linguistic-features#named-entities\" target=\"_new\" rel=\"noopener nofollow\">Spacy Adland\u0131r\u0131lm\u0131\u015f Varl\u0131k Tan\u0131ma<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/tr\/\" target=\"_new\" rel=\"noopener\">OneProxy<\/a>: Proxy sunucular\u0131n\u0131 NER ile birlikte kullanmak i\u00e7in.<\/li>\n<\/ul>","protected":false},"featured_media":468975,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478093","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Named Entity Recognition (NER): A Comprehensive Overview<\/mark>","faq_items":[{"question":"What is Named Entity Recognition (NER)?","answer":"<p>Named Entity Recognition (NER) is a subfield of Natural Language Processing (NLP) that identifies and classifies named entities in text. These entities can include persons, organizations, locations, expressions of times, quantities, monetary values, percentages, and more.<\/p>"},{"question":"What are the main applications of Named Entity Recognition?","answer":"<p>Named Entity Recognition is used in various domains such as information retrieval, machine translation, data mining, search engines, customer support, and healthcare.<\/p>"},{"question":"How does Named Entity Recognition (NER) work?","answer":"<p>The process of NER involves several stages including tokenization, part-of-speech tagging, parsing, and finally identifying and classifying the entities into predefined categories such as names of persons, organizations, locations, etc.<\/p>"},{"question":"What are the key features of Named Entity Recognition (NER)?","answer":"<p>Key features of NER include accuracy in identifying and classifying entities, speed in processing text, scalability, language independence, and adaptability to specific domains or industries.<\/p>"},{"question":"What types of Named Entity Recognition (NER) exist?","answer":"<p>There are several types of NER, including Rule-Based NER, which utilizes predefined grammatical rules, Supervised NER that uses labeled data for training models, Semi-Supervised NER that combines labeled and unlabeled data, and Unsupervised NER that does not require labeled data.<\/p>"},{"question":"What are some problems with Named Entity Recognition, and how can they be solved?","answer":"<p>Some common problems include a lack of labeled data and language-specific constraints. These can be solved by utilizing semi-supervised or unsupervised learning methods and adapting the model to specific languages or domains.<\/p>"},{"question":"What are the future perspectives and technologies related to Named Entity Recognition (NER)?","answer":"<p>Future perspectives include integration with deep learning, adaptability to various languages, and the development of real-time processing capabilities.<\/p>"},{"question":"How can proxy servers be used with Named Entity Recognition (NER)?","answer":"<p>Proxy servers, such as those provided by OneProxy, can be used to scrape data for NER. They allow for efficient and ethical gathering of text data by anonymizing the requests, facilitating the training and implementation of NER models.<\/p>"},{"question":"Where can I find more information about Named Entity Recognition (NER)?","answer":"<p>You can learn more about NER from resources such as Stanford NLP Named Entity Recognizer, NLTK Named Entity Recognition, Spacy Named Entity Recognition, and OneProxy's website for utilizing proxy servers in conjunction with NER.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/478093","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\/478093\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/468975"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=478093"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}