How to build a smart search engine

How to build a smart search engine

In this post, we want to go beyond this and create a truly smart search engine. This post will describe the process to do this and also provide template code to achieve this on any dataset.

In the first post within this series, we built a search engine in just a few lines of code which was powered by the BM25 algorithm used in many of the largest enterprise search engines today.

In this post, we want to go beyond this and create a truly smart search engine. This post will describe the process to do this and also provide template code to achieve this on any dataset.

But what do we mean by ‘smart’? We are defining this as a search engine which is able to:

  • Return relevant results to a user even if they have not searched for the specific words within these results.
  • Be location aware; understand UK postcodes and the geographic relationship of towns and cities in the UK.
  • Be able to scale up to larger datasets (we will be moving to a larger dataset than in our previous example with 212k records but we need to be able to scale to much larger data).
  • Be orders of magnitude faster than our last implementation, even when searching over large datasets.
  • Handle spelling mistakes, typos and previously ‘unseen’ words in an intelligent way.

In order to achieve this, we will need to combine a number of techniques:

  • fastText Word vectors. We will train a model on our data set to create vector representations of words (more information on this here).
  • BM25. We will still be using this algorithm to power our search but we will need apply this to our word vector results.
  • Superfast searching of our results using the lightweight and highly efficient Non-Metric Space Library (NMSLIB).

This will look something like the below:

Image for post

An overview of the pipeline we will be creating in this post

This article will walk through each of these areas and describe how they can be brought together to create a smart search engine.

programming artificial-intelligence towards-data-science python search

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Applied Data Science with Python Certification Training Course -IgmGuru

Master Applied Data Science with Python and get noticed by the top Hiring Companies with IgmGuru's Data Science with Python Certification Program. Enroll Now

Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...

50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.