Lin Zhuoyi

Appointment: PhD student

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1 to 10 of 15 Results

Related data for GLIMG: Global and local item graphs for top-N recommender systems Apr 23, 2022 Lin, Zhuoyi, 2022, "Related data for GLIMG: Global and local item graphs for top-N recommender systems", https://doi.org/10.21979/N9/NRRVDW, DR-NTU (Data), V2 GLIMG: Global and local item graphs for top-N recommender systems
labelml1m.txt Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems Plain Text - 11.8 KB - MD5: 07701e260ae2c69d9d3c9f226c35cabc
labelyelp.txt Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems Plain Text - 11.1 KB - MD5: 2bd81066874f84dcf69bf7e646cfad46
main.py Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems Python Source Code - 8.0 KB - MD5: fef17ebb815014628196c42300145816 Code
Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering Apr 23, 2022 Lin, Zhuoyi, 2022, "Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering", https://doi.org/10.21979/N9/TO2HBX, DR-NTU (Data), V2 Latent factor models play a dominant role among recommendation techniques. However, most of the existing latent factor models assume both historical interactions and embedding dimensions are independent of each other, and thus regrettably ignore the high-order interaction informa...
comet.rar Apr 23, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering RAR Archive - 17.1 KB - MD5: 0fb5991c8bc2b1c5bd3adf8a9a2d5dbc Code
ml-1m.test.negative Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering Unknown - 2.7 MB - MD5: 4dd3924265e2d0e7b2e6734fd7bebc49 Data
ml-1m.test.rating Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering Unknown - 127.9 KB - MD5: 8e5873f99378eca9dcb1981002dbfc79 Data
ml-1m.train.rating Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering Unknown - 20.5 MB - MD5: 97bd887fdcd1c70d3d782dd85f44c3d2 Data
ml1m_test.txt Apr 17, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems Plain Text - 1.4 MB - MD5: afe3adcbc6f8f77060fb7844cc97442c Data

Related data for GLIMG: Global and local item graphs for top-N recommender systems

Apr 23, 2022

Lin, Zhuoyi, 2022, "Related data for GLIMG: Global and local item graphs for top-N recommender systems", https://doi.org/10.21979/N9/NRRVDW, DR-NTU (Data), V2

GLIMG: Global and local item graphs for top-N recommender systems

labelml1m.txt

Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems

Plain Text - 11.8 KB -

labelyelp.txt

Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems

Plain Text - 11.1 KB -

main.py

Apr 23, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems

Python Source Code - 8.0 KB -

Code

Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering

Apr 23, 2022

Lin, Zhuoyi, 2022, "Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering", https://doi.org/10.21979/N9/TO2HBX, DR-NTU (Data), V2

Latent factor models play a dominant role among recommendation techniques. However, most of the existing latent factor models assume both historical interactions and embedding dimensions are independent of each other, and thus regrettably ignore the high-order interaction informa...

comet.rar

Apr 23, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering

RAR Archive - 17.1 KB -

Code

ml-1m.test.negative

Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering

Unknown - 2.7 MB -

Data

ml-1m.test.rating

Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering

Unknown - 127.9 KB -

Data

ml-1m.train.rating

Apr 18, 2022 - Related Data for COMET: Convolutional Dimension Interaction for Collaborative Filtering

Unknown - 20.5 MB -

Data

ml1m_test.txt

Apr 17, 2022 - Related data for GLIMG: Global and local item graphs for top-N recommender systems

Plain Text - 1.4 MB -

Data

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