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Part 1: Document Description
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Citation |
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Title: |
Female Daily Implicit Dataset |
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Identification Number: |
doi:10.34820/FK2/FFIOMB |
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Distributor: |
Telkom University Dataverse |
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Date of Distribution: |
2022-04-01 |
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Version: |
1 |
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Bibliographic Citation: |
TOTO WIBOWO, AGUNG, 2022, "Female Daily Implicit Dataset", https://doi.org/10.34820/FK2/FFIOMB, Telkom University Dataverse, V1 |
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Citation |
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Title: |
Female Daily Implicit Dataset |
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Identification Number: |
doi:10.34820/FK2/FFIOMB |
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Authoring Entity: |
TOTO WIBOWO, AGUNG (Universitas Telkom - Data Science) |
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Distributor: |
Telkom University Dataverse |
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Access Authority: |
TOTO WIBOWO, AGUNG |
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Depositor: |
TOTO WIBOWO, AGUNG |
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Date of Deposit: |
2022-04-01 |
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Study Scope |
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Keywords: |
Computer and Information Science, recommender system, implicit feedback, implicit interaction |
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Abstract: |
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. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Bibliographic Citation: |
"Recommending Product using Non-negative Matrix Factorization with Implicit Feedback Interaction", IndoJC |