Use of topical and temporal profiles and their hybridisation for content-based recommendation
| Autor: | Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
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| Popis: | Funding Funding for open access publishing: Universidad de Granada/CBUA. This work was supported in part by the Spanish “Agencia Estatal de Investigación” under Grant PID2019-106758GB-C31, in part by the Spanish “FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades” under Grant A-TIC-146-UGR20, and in part by the European Regional Development Fund (ERDF-FEDER). In the context of content-based recommender systems, the aim of this paper is to determine how better profiles can be built and how these affect the recommendation process based on the incorporation of temporality, i.e. the inclusion of time in the recommendation process, and topicality, i.e. the representation of texts associated with users and items using topics and their combination. To that end, we build both topically and temporally homogeneous subprofiles to represent items. The main contribution of the paper is to present two different ways of hybridising these two dimensions and to evaluate and compare them with other alternatives. Our proposals and experiments are carried out in the specific context of publication venue recommendation. Funding for open access publishing: Universidad de Granada/CBUA Spanish “Agencia Estatal de Investigación” under Grant PID2019-106758GB-C31 Spanish FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades under Grant A-TIC-146-UGR20 European Regional Development Fund (ERDF-FEDER) |
| Databáze: | OpenAIRE |
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