{"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.34820/FK2/FFIOMB","identifier":"https://doi.org/10.34820/FK2/FFIOMB","name":"Female Daily Implicit Dataset","creator":[{"name":"TOTO WIBOWO, AGUNG","affiliation":"Universitas Telkom - Data Science"}],"author":[{"name":"TOTO WIBOWO, AGUNG","affiliation":"Universitas Telkom - Data Science"}],"datePublished":"2022-04-01","dateModified":"2022-04-01","version":"1","description":["Female daily is a company who bring together expert editors and countless beauty enthusiasts into community via a discovery application. In this dataset, we obtain female daily implicit interaction to be used to recommend beauty product. We have developed and published a NMF based algorithm to generate product recommendation based on the rating prediction. Please kindly cite our publication entitled \"Recommending Product using Non-negative Matrix Factorization with Implicit Feedback Interaction\" on IndoJC."],"keywords":["Computer and Information Science","recommender system, implicit feedback, implicit interaction"],"citation":[{"@type":"CreativeWork","text":"\"Recommending Product using Non-negative Matrix Factorization with Implicit Feedback Interaction\", IndoJC"}],"license":{"@type":"Dataset","text":"CC0","url":"https://creativecommons.org/publicdomain/zero/1.0/"},"includedInDataCatalog":{"@type":"DataCatalog","name":"Telkom University Dataverse","url":"https://dataverse.telkomuniversity.ac.id"},"publisher":{"@type":"Organization","name":"Telkom University Dataverse"},"provider":{"@type":"Organization","name":"Telkom University Dataverse"}}