Tag: Chatbot

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AI-powered Search with spaCy — Part 3

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In the previous articles of this series, you saw some examples of how you might use spaCy’s linguistic features to process user input, extracting the key word or key phrase from it to use then them for a search on the web. In. In the second part, you saw how to handle some complicated cases; for example, you looked at...

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AI-powered Search with spaCy — Part 2

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In the first article of this series, you learned some techniques you might use to process user questions, extracting the key word or phrase from it to perform a search on the web. You saw some examples of how to deal with certain types of user questions, finding the most important pieces of information in it. In this part, you’ll...

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AI-powered Search with spaCy — Part 1

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One of those tasks AI powered application usually faces is the ability to understand what the user is asking about or what he/she wants to know. Actually, it’s a big challenge to make your code “understand’ user questions. In this article, you’ll see an example of how you can create “smart” code that can process a certain type of user...

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Answering Questions Programmatically with Wikipedia API and spaCy

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In the modern world, artificial Intelligence (AI) is almost everywhere. We have long been accustomed to the fact that a robot picks up the phone when you call a bank, and ordering a pizza can be done without human participation. In this article, you’ll see how to create programming code that can intelligently answer user input. For example, it might...

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Using spaCy to Find Sequences of Words Based on Pattern Rules – Part 2

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In the previous part, we discussed how you can take advantage of spaCy’s rule-based matcher engines, using both pattern rules and documents. In this part, you’ll see some examples of the former, based on using linguistic features, such as syntactic dependency labels and simple and extended part of speech tags. Determining Manually a Sequence of Words Satisfying a Pattern Rule...

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Using spaCy to Find Sequences of Words Based on Pattern Rules – Part 1

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spaCy’s rule-based matcher engines are much powerful than just using regular expressions, since those engines allow you to find not only particular words in a submitted text, but also discover their relationships. spaCy provides you with the ability to match sequences of tokens based on both pattern rules and documents. In the first case, you use spaCy’s Matcher object. For...

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Intelligent Text Generation with spaCy Part3

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In this part, we’ll discuss how to convert questions into statements or vice versa. As you know, in English word order in questions differs from word order in statements. You already saw a simple example of translating a question into a statement in part 1 of this article series. In this article, we’ll take a closer look at this problem,...

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Intelligent Text Generation with spaCy Part2

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Word sequence patterns based on linguistic features and introduced in the previous article in this series are not the only means of intelligent text processing and text generation. This article focuses on another common technique based on using syntactic dependency trees. This is also one of those techniques that you can use to teach your conversational application to generate meaningful...

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Using Linguistic Features in NLP

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If you had to describe what NLP is about, what would you point out as the most important thing? Is there something that is vital for many use cases and is employed in almost every NLP application? For example, what do you almost certainly need when it comes to a task of information extraction of any kind? Right. Linguistic features,...

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Intelligent Text Generation with spaCy Part1

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The most challenging tasks in natural language processing are natural language understanding and natural language generation. This article focuses on the latter, giving an example of how you might teach your conversational application to respond properly to its users. Of course, you will not find here a universal solution that covers all possible cases and can be implemented with just...

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