An interpretable music similarity measure based on path interestingness Article Swipe
Giovanni Gabbolini
,
Derek Bridge
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.5624649
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.5624649
We introduce a novel and interpretable path-based music similarity measure. Our similarity measure assumes that items, such as songs and artists, and information about those items are represented in a knowledge graph. We find paths in the graph between a seed and a target item; we score those paths based on their interestingness; and we aggregate those scores to determine the similarity between the seed and the target. A distinguishing feature of our similarity measure is its interpretability. In particular, we can translate the most interesting paths into natural language, so that the causes of the similarity judgements can be readily understood by humans. We compare the accuracy of our similarity measure with other competitive path-based similarity baselines in two experimental settings and with four datasets. The results highlight the validity of our approach to music similarity, and demonstrate that path interestingness scores can be the basis of an accurate and interpretable similarity measure.
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- Type
- paratext
- Language
- en
- Landing Page
- https://doi.org/10.5281/zenodo.5624649
- OA Status
- green
- Cited By
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- 10
- OpenAlex ID
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https://openalex.org/W4226072553Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.5624649Digital Object Identifier
- Title
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An interpretable music similarity measure based on path interestingnessWork title
- Type
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paratextOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-11-07Full publication date if available
- Authors
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Giovanni Gabbolini, Derek BridgeList of authors in order
- Landing page
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https://doi.org/10.5281/zenodo.5624649Publisher landing page
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.5281/zenodo.5624649Direct OA link when available
- Concepts
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Measure (data warehouse), Similarity (geometry), Similarity measure, Artificial intelligence, Computer science, Path (computing), Pattern recognition (psychology), Data mining, Image (mathematics), Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2022: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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