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Python Natural Language Processing Cookbook

You're reading from Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

Product type Paperback

Published in Mar 2021

Publisher Packt

ISBN-13 9781838987312

Length 284 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Mobile Application Development

Author (1):

Zhenya Antić

View More author details

Table of Contents (10) Chapters

Preface

1. Chapter 1: Learning NLP Basics

2. Chapter 2: Playing with Grammar FREE CHAPTER

3. Chapter 3: Representing Text – Capturing Semantics

4. Chapter 4: Classifying Texts

5. Chapter 5: Getting Started with Information Extraction

6. Chapter 6: Topic Modeling

7. Chapter 7: Building Chatbots

8. Chapter 8: Visualizing Text Data

9. Other Books You May Enjoy

Getting started with semantic search

In this recipe, we will get a glimpse of how to get started on expanding search with the help of a word2vec model. When we search for a term, we expect the search engine to show us a result with a synonym when we didn't use the exact term contained in the document. Search engines are far more complicated than what we'll show in the recipe, but this should give you a taste of what it's like to build a customizable search engine.

Getting ready

We will be using an IMDb dataset from Kaggle, which can be downloaded from https://www.kaggle.com/PromptCloudHQ/imdb-data. Download the dataset and unzip the CSV file.

We will also use a small-scale Python search engine called Whoosh. Install it using pip:

pip install whoosh

We will also be using the pretrained word2vec model from the Using word embeddings recipe.

How to do it…

We will create a class for the Whoosh search engine that will create a document index based...

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Authors (1)

Zhenya Antić

Zhenya Antić

Zhenya Antić, Ph.D. is an expert in AI and NLP. She is currently the Director of AI Automation at Arch Insurance, where she leads initiatives in Intelligent Document Processing and applies various AI solutions to complex problems. With extensive consulting experience, Zhenya has worked on numerous NLP projects with various companies. She holds a Ph.D. in Linguistics from the University of California, Berkeley, and a B.S. in Computer Science from the Massachusetts Institute of Technology.

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