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A Novel Framework for Top-N Recommendation Based on Non-negative Matrix Tri-Factorization

Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018(2019)10.1007/978-981-13-3402-3_36Source: DataRank Database

A Novel Framework for Top-N Recommendation Based on Non-negative Matrix Tri-Factorization is a research paper published in Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018 (2019). On theSindex it has a DataRank of 0.104. It has been cited 1 time.

N/A

0.104DataRank · unranked

Scored on demand from live citation data

1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Impact (FWCI 0.00)OA: closedTopics (20)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.104

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (2)

Yingnan Qu,Jin Tian ORCID

Live enrichment

PubMed:26207759 OpenAlex:https://openalex.org/W2909865466

FWCI

0.00

Citation Percentile

0.0%

Citation Trend

2025

closedLicense: http://www.springer.com/tdm

publisherhttp://link.springer.com/content/pdf/10.1007/978-981-13-3402-3_36

https://doi.org/10.1007/978-981-13-3402-3_36

Fields of Study

Recommender Systems and TechniquesImage Retrieval and Classification TechniquesAdvanced Computing and Algorithms

Keywords

Collaborative filteringRecommender systemMatrix decompositionComputer scienceScalabilityBlock matrixCluster analysisInformation retrievalBiclusteringBlock (permutation group theory)Theoretical computer scienceData miningArtificial intelligenceDatabaseMathematicsCombinatoricsFuzzy clustering

A Novel Framework for Top-N Recommendation Based on Non-negative Matrix Tri-Factorization

FAIR Checklist

DataRank Breakdown

Authors (2)

Impact

Open Access

Topics