How Search Engines like Google Retrieve Results: Introduction to Information Extraction using Python and spaCy
Overview
- How do search engines like Google understand our queries and provide relevant results?
- Learn about the concept of information extraction
- We will apply information extraction in Python using the popular spaCy library – so a lot of hands-on learning is ahead!
Introduction
I rely heavily on search engines (especially Google) in my daily role as a data scientist. My search results span a variety of queries – Python code questions, machine learning algorithms, comparison of Natural Language Processing (NLP) frameworks, among other things.
I’ve always been curious about how these search engines understand my query and extract the relevant results as if they know what I am thinking.
I wanted to understand how the NLP aspect works here – basically, how does the algorithm understand unstructured text data and convert that into structured data and show me relevant results?
Let’s take an example. I entered two different queries on Google:
