This document summarizes a research paper that proposes using content-based similarity between songs to help annotate large music collections. The researchers aim to address problems like sparse tagging and the "cold start" of new songs with no tags. Their approach uses audio features to find similar songs and then propagates their tags as suggestions to ease the annotation process. They conducted experiments comparing automatically propagated tags to ground truth tags on over 5,000 songs, finding reasonable recall and precision especially when limiting tags to mood descriptors. The document outlines their methodology, experimental results and conclusions.

7. our proposal Annotated