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Weight-Based Dynamic Hybrid Recommendation System for Web Application Content

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dc.contributor.authorJerónimo, Margarida
dc.contributor.authorPinto, Filipe C.
dc.contributor.authorP. Duarte, Rui
dc.date.accessioned2023-06-26T09:17:19Z
dc.date.available2023-06-26T09:17:19Z
dc.date.issued2023
dc.description.abstractThis paper presents a prototype for a web application recommendation system’s content applied to movies’ recommendations. It learns the pattern of user content consumption, predicting what he will consume in the future based on similar items to those he has shown interest. It considers similarity with neighbor users, thus creating a user model. Content-based filtering, collaborative filtering, and memory-based on hybrid filtering techniques are used. Content-based filtering allows to extract the fundamental features or attributes of the items and select similar items. Moreover, it proposes predicted classifications for the items of interest not yet classified by the active user. Collaborative filtering allows applying the kNN methodology to identify the similarity between the active user located in the neighborhood and propose predicted classifications for items of interest not yet classified. Hybrid filtering combines the two methodologies to overcome their drawbacks. A weighted approach is applied, allowing a dynamic linear combination of collaborative and content-based filtering. The results obtained were empirically relevant in the experimental evaluation, matching with the results presented in similar studies validated with RMSE metrics.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationJerónimo, M., Pinto, F.C., Duarte, R.P. (2023). Weight-Based Dynamic Hybrid Recommendation System for Web Application Content. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Seventh International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 464. Springer, Singapore. https://doi.org/10.1007/978-981-19-2394-4_2pt_PT
dc.identifier.doi10.1007/978-981-19-2394-4_2pt_PT
dc.identifier.isbn978-981-19-2394-4
dc.identifier.urihttp://hdl.handle.net/10400.19/7821
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationThis work is funded by National Funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the project Ref. UIDB/05583/2020pt_PT
dc.subjectInformation systemspt_PT
dc.subjectRecommender systemspt_PT
dc.subjectHuman centered computingpt_PT
dc.subjectUser Modelspt_PT
dc.subjectWeb-based interactionpt_PT
dc.titleWeight-Based Dynamic Hybrid Recommendation System for Web Application Contentpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage17pt_PT
oaire.citation.startPage9pt_PT
oaire.citation.titleProceedings of Seventh International Congress on Information and Communication Technology. Lecture Notes in Networks and Systemspt_PT
oaire.citation.volume464pt_PT
person.familyNameJerónimo
person.familyNameMonteiro Amaro Duarte
person.givenNameMargarida
person.givenNameRui Pedro
person.identifiergIYE8M4AAAAJ
person.identifier.ciencia-id211F-55A0-4B63
person.identifier.orcid0000-0001-5745-5127
person.identifier.orcid0000-0002-6819-0985
person.identifier.scopus-author-id14059938600
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication14c7de26-3832-4ae0-8565-09f7a5777ce7
relation.isAuthorOfPublicationd56c3162-80a4-4ade-810d-43bae4ee6d73
relation.isAuthorOfPublication.latestForDiscovery14c7de26-3832-4ae0-8565-09f7a5777ce7

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