A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation

Nikolaos Polatidis; Elias Pimenidis; Andrew Fish; Stelios Kapetanakis

doi:10.1142/S021821301960011X

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation

Nikolaos Polatidis, Elias Pimenidis, Andrew Fish, Stelios Kapetanakis

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	1960011
Journal	International Journal on Artificial Intelligence Tools
Volume	28
Issue number	8
DOIs	https://doi.org/10.1142/S021821301960011X
Publication status	Published - 4 Dec 2019

Keywords

Recommender systems
Evaluation
Reproducibility
Replication

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10.1142/S021821301960011X

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluationAccepted author manuscript, 297 KB

Nikolaos Polatidis
- N.Polatidisbrighton.acuk
- School of Arch, Tech and Eng - Principal Lecturer
Person: Academic

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title = "A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation",

keywords = "Recommender systems, Evaluation, Reproducibility, Replication",

author = "Nikolaos Polatidis and Elias Pimenidis and Andrew Fish and Stelios Kapetanakis",

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doi = "10.1142/S021821301960011X",

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AU - Polatidis, Nikolaos

AU - Pimenidis, Elias

AU - Fish, Andrew

AU - Kapetanakis, Stelios

PY - 2019/12/4

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KW - Recommender systems

KW - Evaluation

KW - Reproducibility

KW - Replication

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DO - 10.1142/S021821301960011X

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JO - International Journal on Artificial Intelligence Tools

JF - International Journal on Artificial Intelligence Tools

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M1 - 1960011

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A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation

Keywords

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Profiles

Nikolaos Polatidis

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