Creating a Semantic Search Algorithm to Understand User Intent and Context, Improving Search Precision and Relevance

This Omdena Local Chapter Challenge runs for 8 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Jordan Chapter.

The problem

The current search system faces several limitations, including:

• Lack of Contextual Understanding: The existing search engine primarily relies on keyword matching, resulting in a limited contextual understanding of user queries. As a result, the search results often fail to capture the user’s intent accurately.
• Inaccurate and Irrelevant Results: Keyword-based searches can produce irrelevant or partially relevant results, leading to user frustration and diminished trust in the search functionality.

The goals

The Omdena Jordan Chapter team’s goal is to create a powerful semantic search algorithm that comprehends user intent and context, enhancing search accuracy and relevance. They will design a user-friendly interface, optimize performance, and uphold ethical AI practices. Leveraging GPT-3 or any newer versions available, they will generate data to build the semantic search system.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work