Generating interesting song-to-song segues with Dave
dc.contributor.author | Gabbolini, Giovanni | |
dc.contributor.author | Bridge, Derek G. | |
dc.contributor.funder | Science Foundation Ireland | en |
dc.contributor.funder | European Regional Development Fund | en |
dc.date.accessioned | 2021-08-03T12:08:04Z | |
dc.date.available | 2021-08-03T12:08:04Z | |
dc.date.issued | 2021-06-21 | |
dc.date.updated | 2021-08-03T11:23:45Z | |
dc.description.abstract | We introduce a novel domain-independent algorithm for generating interesting item-to-item textual connections, or segues. Pivotal to our contribution is the introduction of a scoring function for segues, based on their ‘interestingness’. We provide an implementation of our algorithm in the music domain. We refer to our implementation as Dave. Dave is able to generate 1553 different types of segues, that can be broadly categorized as either informative or funny. We evaluate Dave by comparing it against a curated source of song-to-song segues, called The Chain. In the case of informative segues, we find that Dave can produce segues of the same quality, if not better, than those to be found in The Chain. And, we report positive correlation between the values produced by our scoring function and human perceptions of segue quality. The results highlight the validity of our method, and open future directions in the application of segues to recommender systems research. | en |
dc.description.sponsorship | Science Foundation Ireland (Grant number 12/RC/2289-P2) | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Accepted Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Gabbolini, G. and Bridge, D. (2021) 'Generating interesting song-to-song segues with Dave', UMAP 2021 - Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Utrecht, Netherlands, 21-25 June, pp. 98-107. doi: 10.1145/3450613.3456819 | en |
dc.identifier.doi | 10.1145/3450613.3456819 | en |
dc.identifier.endpage | 107 | en |
dc.identifier.isbn | 978-1-4503-8366-0 | |
dc.identifier.startpage | 98 | en |
dc.identifier.uri | https://hdl.handle.net/10468/11632 | |
dc.language.iso | en | en |
dc.publisher | Association for Computing Machinery | en |
dc.relation.uri | https://www.um.org/umap2021/ | |
dc.rights | © 2021, the Authors. For the purpose of Open Access, the authors have applied a CC BY public copyright licence to this Author Accepted Manuscript. The definitive Version of Record was published in UMAP '21: Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization: https://doi.org/10.1145/3450613.3456819. | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | Interestingness | en |
dc.subject | Recommender systems | en |
dc.subject | Segues | en |
dc.subject | User studies | en |
dc.title | Generating interesting song-to-song segues with Dave | en |
dc.type | Conference item | en |
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