Learning languages with the help of algorithms
SMRTR summary
When learning a new language through reading, finding books with maximum vocabulary impact can be optimized using algorithms. While selecting the single best book is computationally simple, choosing the optimal set of k books becomes an NP-hard problem as k increases. Fortunately, this challenge can be addressed using approximation algorithms like greedy approaches, which add high-impact books one at a time with reasonable accuracy guaranteed within certain bounds of the optimal solution.
SMRTR provides this summary for quick context. The original article belongs to John D. Cook.
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