Tag: dependency parsing

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AI-powered Search with spaCy – Part 9

In the previous parts, you’ve learned a lot about how to use linguistics features in spaCy to interpret a user query’s intent. Continuing with this topic in this part, we’ll cover to extract intent from user input, using different pattern based on syntactic dependency labels. As a quick refresher, we’ll look at the role of the direct object/transitive verb pair…...

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AI-powered Search with spaCy – Part 8

In the previous articles in this series, you’ve learned a lot of different techniques that might be used for modifying a search string submitted by a user to a search engine, in order to obtain more relevant results. Thus, for example, you looked at how to find noun chunks and enclose them in double quotes in part 7, and how…...

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AI-powered Search with spaCy – Part 6

Summarizing all those examples you have seen in the previous articles in this series, you should have already a good grasp of how the most common types of request sentences might be processed to extract the phrase that is most relevant for feeding a search engine. Just to recap, you have seen examples that rely on using linguistic features extracted…...

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AI-powered Search with spaCy – Part 5

So far, you have seen examples that rely on linguistic features associated with individual words in a sentence, when extracting the most descriptive phrase from that sentence. Very often however, you might need to extract the entire chunks to work with. For example, in the following sentence: “How to use Oracle Database 19c from a Python script.”, you might want…...

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AI-powered Search with spaCy — Part 4

In the previous articles in this series, you learned how interrogative sentences of the most common types can be parsed, allowing you to extract the most descriptive words from a sentence to be used then for a search for a relevant answer. In other words, you learned to implement the ability to understand what the user is asking about or…...

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AI-powered Search with spaCy — Part 3

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

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

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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