Abstract
We present a new way of accessing large sets of musical
artists based on high-level concepts. The concepts are derived
and assigned to individual artists by an automatic procedure:
Using a list of music-related words and phrases, the
well-known TF×IDF approach is applied to analyse the 100
top web pages related to each artist, as delivered by a web
search engine. This data then is decomposed into a number
of archetypical bases or concepts by Non-Negative
Matrix Factorisation (NMF). Each artist is then described
by the amount by which it is related to each of these concepts.
In our browser application presented here, such a representation
allows for independently adjusting the weight of
each of these concepts, to recommend those artists that best
match the desired query profile.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 5th International Workshop on Content Based Multimedia Indexing (CBMI 2007) |
| Number of pages | 8 |
| Publication status | Published - 2007 |
Fields of science
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
- 202002 Audiovisual media