Tag: Natural Language Processing

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Title: AI-powered Search with spaCy — Part 14

As you learned in the previous part of this series, guessing what is in a photo is perhaps one of the most interesting and yet challenging tasks of AI, which involves both Computer Vision and NLP. In this article, as well as in the previous two in this series, we concentrate on the NLP techniques that you might use to…...

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AI-powered Search with spaCy – Part 12

In this part, we’ll look at how you might find some phrases in a text, which contain words from a predefined list. For example, you may have a set of descriptive tags generated for a photo by a computer vision platform. Such a set of tags might be useful for image classification and you might use it as the basis…...

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AI-powered Search with spaCy – Part 11

In this part, we’ll look at how you might intelligently reduce the sentence when preparing a phrase for a search from it. In particular, you’ll see how to reduce the sentences containing an adverbial clause modifier or an open clausal complement. Say, you have the following sentence as an input: ‘I talked to him to secure the account.’ In this…...

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AI-powered Search with spaCy – Part 10

In this tenth part in the series, we are continuing to discuss how you might take advantage of linguistic features available in spaCy. In particular, we’ll look at how you might obtain necessary information related to the task of meaning extraction, when it comes to understanding of user input coming in the form of request utterances. From the previous parts,…...

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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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