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Saves human staff/resourcesBots don’t get tired of answering repetitive questions, or inquiries like human staff do.

Quicker processesAn ai chatbot isn’t limited by the number of conversations and can respond to multiple prospects simultaneously.

It makes the whole process more efficient and faster.How do they Function?Now let’s discuss how exactly chatbots function and what helps in smart Chatbot development.

The moment any question or query is presented to a bot, complex algorithms process the input and understand the query’s right tone and context.

Whereas, during the Chatbot development process, your bot’s intelligence will depend on the way you apply machine learning while deploying the bot in your systems.Moreover, if you want to know deeply about the whole Chatbot development process, it is not enough to know only about technology.

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The insights can be different:

Valuable information in the text through semantic search (such as quotations, key facts, et al.)

Specific details about a certain subject (figures, states, etc)

Mentions of specific things in the texts (name mentions and so on)

The process looks like this:

Information Extraction to get a hold on the unstructured text

As human-generated data has exponentially increased on many platforms, it has become impossible for the businesses to check or interact with that data manually, here the applications of NLP take charge.For example, if a business wants to check the reviews of their new product and make inferences from it, allotting people for reading the reviews and categorizing them will be inefficient, as there are lakhs of reviews.

These chatbots can be customized for a specific market like Kotak Mahindra Bank now uses Keya as its virtual assistant.How NLP works?Making sense of the syntax is one of the most critical things for applying NLP algorithms; some of the syntax analysis methods are:Lemmatization: It means reducing the various inflected forms of a word into a single form for a more straightforward analysis.Morphological segmentation: It involves dividing words into individual units called morphemes.Word segmentation: It consists of dividing a large piece of continuous text into distinct units.Part-of-speech tagging: It involves identifying the part of speech for every word.Parsing: It consists in undertaking a grammatical analysis for the provided sentence.Sentence breaking: It consists in placing sentence boundaries on a large piece of text.Stemming: It involves cutting the inflected words to their root form.Morphological segmentation: It consists of dividing words into individual units called morphemes.Word segmentation: It consists of dividing a large piece of continuous text into distinct units.Part-of-speech tagging: It involves identifying the part of speech for every word.Parsing: It involves undertaking a grammatical analysis for the provided sentence.Sentence breaking: It involves placing sentence boundaries on a large piece of text.Stemming: It involves cutting the inflected words to their root form.Open-source libraries for NLPThere are many NLP libraries on the internet, some of the most popular libraries are:NLTK: It is the most featured library; the most used combination is nltk(Natural Language Toolkit) and python.

This library is for production usage, written in the programming language Cython; it provides the fastest syntactic parser in the market.

Although the menu of this library is limited, there are fewer choices.TextBlob: This library is an extension of nltk.

This library is suitable for smaller projects.Saas Tools for NLPPeople want to generate insights from texts, but don’t want to delve deeper into the working, some of the tools for non-technical people are:Amazon Comprehend: Amazon Comprehend is a natural language processing software that uses machine learning to look for insights and relationships within a text.

Advertising companies analyze the digital footprints of a user to predict their potential audience interested in their products.NLP software helps increase the range of channels for ad placement.Healthcare is entering a new era with NLP applications, data mining integration in healthcare systems helps doctors make more well-informed decisions and improve diagnosis, and patient treatment.Chatbots are a prime example of automation tech.

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Artificial intelligence (AI) and machine learning are becoming more integrated in many aspects of social media. AI is far from replacing human touch in the field of social media, but it is increasing both the quantity and quality of online interactions between businesses and their customers.

This article discusses 4 machine learning tools that can enhance social media marketing: social media monitoring, sentiment analysis, image recognition, and chatbots. The article includes real-life examples of how major businesses such as UNIQLO, The Container Store, GameStop, Airbnb, and Estee Lauder are actually using these machine learning techinques on their Facebook, Twitter, and Instagram accounts to build relationships with their customers through social media.