Amazon Technologies, Inc.

Zaur Kambarov

Tom Killalea

Janna Hamaker

Amit D Agarwal

Eugene Kalenkovich

As described herein, passages in a digital work (e.g., eBook, music, movie, picture, etc.) may be highlighted and questions pertaining to those highlights may be developed. The highlights are collected centrally and subsequently supplied to users along with the digital works. Users may further ask questions pertaining to the highlighted passages, and these questions are associated with the highlights. Answers to the questions may also be discovered and provided to the users.

Questions on highlighted passages

Similarities are discovered among different users with respect to their media experiences and other behaviors, such as taste in media items (e.g., books, music, movies, magazines, art, etc.), browsing behavior, purchase decisions, and online shopping habits, and usage history. The similarities are determined in part by substantially real-time comparison of individual users with a set of predetermined user-based clusters formed from the experiences and behaviors of sample users. Users from a population may then be identified based on similarity metrics. Recommendations for new media items, or other goods/services, may also be made based on choices being made by similar users.

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Seattle, WA, United States of America

Zaur Kambarov