Solving Methods

Average solving time : 0.5 seconds (with filtered model)

In this project, I’ve implemented several methods to solve Cemantix. Here’s how the current approach works:

1. I request the score for a set of starting words (defined in the configuration file) using parallelization.

2. Using NumPy, I compute the cosine similarity between every word and the starting words.

3. I then filter and save the words whose cosine similarity is approximately equal to the score of the starting words (within a small epsilon).

4. For each word identified in step 3, I request its Cemantix score:

   • If the score is 1.0, the solution has been found and the process stops.

   • If not, the process continues with the next candidate.

If no word reaches a score of 1.0, it means the target word is likely not present in my model, and I cannot solve the daily Cemantix puzzle.

Old solving methods

• Beam Solving
• Local Score Solving