{"id":18965,"date":"2025-02-10T15:14:13","date_gmt":"2025-02-10T15:14:13","guid":{"rendered":"https:\/\/mckajim.robisearchltd.co.ke\/?p=18965"},"modified":"2025-06-28T06:22:13","modified_gmt":"2025-06-28T06:22:13","slug":"natural-language-processing-chatbot-nlp-in-a-5","status":"publish","type":"post","link":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/2025\/02\/10\/natural-language-processing-chatbot-nlp-in-a-5\/","title":{"rendered":"Natural Language Processing Chatbot: NLP in a Nutshell"},"content":{"rendered":"<p><h1>Creating ChatBot Using Natural Language Processing in Python Engineering Education EngEd Program<\/h1>\n<\/p>\n<p><img decoding=\"async\" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' 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width=\"302px\" alt=\"nlp based chatbot\"\/><\/p>\n<p><p>The next step in the process consists of the chatbot differentiating between the intent of a user\u2019s message and the subject\/core\/entity. In simple terms, you can think of the entity as the proper noun involved in the query, and intent as the primary requirement of the user. Therefore, a chatbot needs to solve for the intent of a query that is specified for the entity.<\/p>\n<\/p>\n<p><p>Programmers have integrated various functions into NLP technology to tackle these hurdles and create practical tools for understanding human speech, processing it, and generating suitable responses. Needless to say, for a business with a presence in multiple countries, the services need to be just as diverse. An NLP chatbot that is capable of understanding and conversing in various languages makes for  an efficient solution for customer communications. This also helps put a user in his comfort zone so that his conversation with the brand can progress without hesitation.<\/p>\n<\/p>\n<p><h2>The New Chatbots: ChatGPT, Bard, and Beyond<\/h2>\n<\/p>\n<p><p>Chatbots are widely used for customer support due to their ability to handle frequently asked questions and provide quick responses. However, chatbots have diverse applications beyond customer support, such as virtual assistants, sales support, and information retrieval. While chatbots excel at handling straightforward queries, they may face difficulties with more complex or ambiguous user inquiries. Complex queries often require deeper comprehension, reasoning, and problem-solving abilities, which are still areas of improvement for chatbot technology.<\/p>\n<\/p>\n<p><p>The best approach towards NLP that is a blend of Machine Learning and Fundamental Meaning for maximizing the outcomes. Machine Learning only is at the core of many NLP platforms, however, the amalgamation of fundamental meaning and Machine Learning helps to make efficient NLP based chatbots. Machine Language is used to train the bots which leads it to continuous learning for natural language processing (NLP) and natural language generation (NLG). Best features of both the approaches are ideal for resolving the real-world business problems. To create a conversational chatbot, you could use platforms like Dialogflow that help you design chatbots at a high level.<\/p>\n<\/p>\n<p><h2>Multilingual and Cross-Cultural Support<\/h2>\n<\/p>\n<p><p>The quality and quantity of training <a href=\"https:\/\/www.metadialog.com\/blog\/nlp-for-building-a-chatbot\/\">data directly<\/a> impact the accuracy and effectiveness of chatbot responses. Curating and maintaining high-quality training data requires significant effort and resources. Additionally, chatbots need to be constantly updated with new data to ensure their responses remain up-to-date and relevant. The dependency on data presents a challenge in terms of data acquisition, cleaning, and ongoing maintenance. Natural Language Processing (NLP) is a  subfield of AI that focuses on the interaction between computers and human language.<\/p>\n<\/p>\n<div style='border: black dashed 1px;padding: 11px;'>\n<h3>The ChatBot revolution: it&#8217;s more than just small talk &#8211; ZME Science<\/h3>\n<p>The ChatBot revolution: it&#8217;s more than just small talk.<\/p>\n<p>Posted: Fri, 06 Oct 2023 07:00:00 GMT [<a href='https:\/\/news.google.com\/rss\/articles\/CBMiWGh0dHBzOi8vd3d3LnptZXNjaWVuY2UuY29tL3NjaWVuY2UvdGhlLWNoYXRib3QtcmV2b2x1dGlvbi1pdHMtbW9yZS10aGFuLWp1c3Qtc21hbGwtdGFsay_SAQA?oc=5' rel=\"nofollow\">source<\/a>]<\/p>\n<\/div>\n<p><p>We will be using the BeautifulSoup4 library to parse the data from Wikipedia. Furthermore, Python&#8217;s regex library, re, will be used for some preprocessing tasks on the text. Vincent Kimanzi is a driven and innovative engineer pursuing a Bachelor of Science in Computer Science. He is passionate about developing technology products that inspire and allow for the flourishing of human creativity.<\/p>\n<\/p>\n<p><p>In this guided project &#8211; you&#8217;ll learn how to build an image captioning model, which accepts an image as input and produces a textual caption as <a href=\"https:\/\/www.metadialog.com\/blog\/nlp-for-building-a-chatbot\/\">the output.<\/a> We sort the list containing the cosine similarities of the vectors, the second last item in the list will actually have the highest cosine (after sorting) with the user input. The last item is the user input itself, therefore we did not select that. In the previous article, I briefly explained the different functionalities of the Python&#8217;s Gensim library. Until now, in this series, we have covered almost all of the most commonly used NLP libraries such as NLTK, SpaCy, Gensim, StanfordCoreNLP, Pattern, TextBlob, etc.<\/p>\n<\/p>\n<p><img decoding=\"async\" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' 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width=\"306px\" alt=\"nlp based chatbot\"\/><\/p>\n<p><p>Read more about <a href=\"https:\/\/www.metadialog.com\/\">https:\/\/www.metadialog.com\/<\/a> here.<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Creating ChatBot Using Natural Language Processing in Python Engineering Education EngEd Program The next step in the process consists of the chatbot differentiating between the intent of a user\u2019s message and the subject\/core\/entity. In simple terms, you can think of the entity as the proper noun involved in the query, and intent as the primary [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[65],"tags":[],"class_list":["post-18965","post","type-post","status-publish","format-standard","hentry","category-ai-news"],"_links":{"self":[{"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/posts\/18965","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/comments?post=18965"}],"version-history":[{"count":1,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/posts\/18965\/revisions"}],"predecessor-version":[{"id":18966,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/posts\/18965\/revisions\/18966"}],"wp:attachment":[{"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/media?parent=18965"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/categories?post=18965"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mckajim.robisearchltd.co.ke\/index.php\/wp-json\/wp\/v2\/tags?post=18965"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}