New explanations based on positive signals in watched content

[sjay8]

Enhanced Explanation Generation in produce_explanation.py:

• Currently, the top history function relied solely on whether a user watched a piece of content. However, watching something doesn’t necessarily mean they enjoyed it.
• A new joint function include more specific explanations based on positive watching signals
  • Explicit Signal – When a user gives a thumbs up to a title.
  • Implicit Signal – When a user watches more than 80% of the content.
  • if present, returns explicit explanation, then implicit, and finally default explanation
• Kept the original watched function in the code for flexibility

Synthetic Data Updates in make_data.py:

• Updated data generation to include artificial liked and watched data.
• Assumed that only 30% of watched content receives an explicit like.
• Used random.choice to select four random numbers, ensuring that two of them are greater than 0.80, simulating implicit engagement.