<\/span><\/h2>\nStop word removal removes all filler and unimportant words from the text like \u2018the\u2019, \u2018is\u2019, \u2018of\u2019, etc. This is done to help focus on more important and meaningful words from the text.<\/p>\n
As a note – stemming, lemmatization and stop word removal can be combined into a single category called text normalization<\/strong>. The purpose of normalizing text is to make the input text consistent and uniform so it can be easily utilized by the NLP software.<\/p>\n<\/span>\u00a0Natural Language Processing (NLP) tasks<\/span><\/h2>\n<\/span>\u2666 Part-of-speech tagging<\/span><\/h2>\nNouns, pronouns, verbs, adverbs, adjectives, etc. are what we call as parts of speech. They tell us about how a word functions within a sentence. Part-of-speech tagging is a technique used by NLP for tagging each word in the input text with a part of speech to better understand their meaning.<\/p>\n
<\/span>\u2666 Word sense disambiguation<\/span><\/h2>\nNLP uses this technique to identify the correct meaning of a word with multiple meanings. For example, consider two sentences:<\/p>\n
\n- He sat on the bank of the river.<\/li>\n
- She deposited some money in the bank.<\/li>\n<\/ol>\n
Both use the word \u2018bank\u2019 but in different contexts. Word-sense disambiguation identifies the first \u2018bank\u2019 as \u2018riverside\u2019 and the second one as a \u2018financial institution\u2019.<\/p>\n
<\/span>\u2666 Sentiment analysis<\/span><\/h2>\nAs the name suggests, sentiment analysis is about interpreting the sentiment or emotion behind a text. It can classify the text into positive, negative or neutral and even detect emotions. It’s mainly used in analyzing customer reviews and feedback.<\/p>\n
<\/span>\u2666 Machine translation<\/span><\/h2>\nMachine translation involves translating text-based or speech-based data from one language to another while maintaining their original meaning. It requires the use of suitable words and correct grammar from the output language.<\/p>\n
<\/span>\u2666 Text generation<\/span><\/h2>\nOne of the most popular features of NLP is text generation. It’s used in generative AIs like ChatGPT and Google’s Gemini for generating a wide range of texts from poetry to blog articles and computer codes.<\/p>\n
Named-entity recognition<\/p>\n
This process works to classify names or nouns in a text into categories like people, location, dates, organizations, etc. For example<\/strong>, let’s take a sentence\u2026<\/p>\n\u2018Michael gave his book to James\u2019<\/p>\n
Here, named-entity recognition classifies \u2018Michael\u2019 and \u2018James\u2019 as a person. Moreover, it also correctly links \u2018his\u2019 to \u2018Michael\u2019.<\/p>\n
<\/span>Challenges and limitations of Natural Language Processing(NLP)<\/span><\/h2>\n\n- NLP relies heavily on the data it is trained on. If it was fed biased or incorrect data during training, it may produce such outputs later as well.<\/li>\n
- Semantic analysis or the understanding of meanings is the strength as well as the limitation of NLP. Although it has high accuracy, it is still limited to the use of words whether text or audio. It cannot grasp alternative forms of communication like body language or voice modulation.<\/li>\n
- NLP may misinterpret or fail to process highly complex inputs that are full of slang, sarcasm or ambiguity.<\/li>\n<\/ul>\n
<\/span>Conclusion<\/span><\/h2>\nNatural language processing is no doubt, a game-changer in the field of AI and machine learning. From simple data analysis and automation, NLP has led machines into the complex arena of understanding human language along with its subtleties. By enabling computers to process and interpret text and speech as humans do, NLP has opened up a new possibility for communication between humans and machines. At this pace, it is possible that one day NLP-powered AI software will be able to breach its limitations and be able to empathize with humans on a deeper level.<\/p>\n","protected":false},"excerpt":{"rendered":"
Table of Contents What is Natural Language Processing (NLP)?What is Natural Language Processing (NLP)?Benefits of Natural Language Processing (NLP)Real-life examples of Natural Language Processing (NLP)How does NLP work\u00a0Natural Language Processing(NLP) Preprocessing\u2666 Tokenization\u2666 Stemming & Lemmatization\u2666 Stop word removal\u00a0Natural Language Processing (NLP) tasks\u2666 Part-of-speech tagging\u2666 Word sense disambiguation\u2666 Sentiment analysis\u2666 Machine translation\u2666 Text generationChallenges and limitations […]<\/p>\n","protected":false},"author":15,"featured_media":10578,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[440,442,439],"tags":[541,643,1085,773,1086],"class_list":["post-10394","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-latest","category-news","tag-ai","tag-chatgpt","tag-natural-language-processing","tag-nlp","tag-search-engine"],"aioseo_notices":[],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/posts\/10394","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/comments?post=10394"}],"version-history":[{"count":5,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/posts\/10394\/revisions"}],"predecessor-version":[{"id":10580,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/posts\/10394\/revisions\/10580"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/media\/10578"}],"wp:attachment":[{"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/media?parent=10394"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/categories?post=10394"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devopscurry.com\/wp-json\/wp\/v2\/tags?post=10394"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}