Finishing 3rd Out of 6,000 in a HackerRank AI Challenge in 30 Minutes
The author finished 3rd out of around 6,000 competitors in a HackerRank AI challenge, with the final solution coming together in just 30 minutes. The article discusses the author's approach, including using context scoring and simple intent rules for common question types.
Why it matters
The article demonstrates how combining a few solid ideas can outperform more complex algorithms in certain AI/ML challenges, highlighting the value of strategic problem-solving.
Key Points
- 1Used context scoring instead of just keyword overlap to improve accuracy
- 2Added simple intent rules for common question types to break ties
- 3Leveraged techniques like keyword positions and sentence-level matching
Details
The article describes the author's approach to a HackerRank challenge in the AI and Machine Learning track. The challenge involved matching questions to their answers within a given paragraph of text. The author found that a naive keyword-based approach was not sufficient, as it broke down when multiple answer options shared similar wording. Instead, the author used a more sophisticated context scoring method, considering factors like keyword overlap within the same sentence, keyword proximity in the local window around the answer, and distance between question keywords and the answer location. Additionally, the author added simple intent-based rules to handle common question types, such as preferring numeric answers for 'how far' or 'how long' questions. These techniques allowed the author to quickly assemble a solution that placed them in the top 3 out of around 6,000 competitors.
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