Which pioneering algorithm fundamentally transformed book retail and became the foundation for modern literary recommendation systems?

In today's publishing industry, major bookstores and online retailers use sophisticated algorithms to personalize recommendations and influence which books become bestsellers. These systems analyze reader behavior patterns and purchasing history to create tailored experiences. But how well do you understand the mechanisms that might be determining your next literary discovery? Test your knowledge about the intersection of retail personalization and the book industry!

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Amazon's 'item-to-item collaborative filtering' (developed in 1998)
Barnes & Noble's 'BookMatch' preference mapping (developed in 2001)
Borders' 'ReaderConnect' purchase pattern analysis (developed in 1997)
Goodreads' 'LitSimilarity' content-based filtering (developed in 2003)