NUS-WIDE

doi:doi:10.57702/85y9yozb

NUS-WIDE

The dataset used in the paper is a multi-view clustering dataset, which contains 6 views of 30000 samples each. The dataset is used to evaluate the performance of the proposed multi-view clustering algorithm.

BibTex:

@dataset{Tat-Seng_Chua_and_Jinhui_Tang_and_Richang_Hong_and_Haojie_Li_and_Zhiping_Luo_and_Yan-Tao_Zheng_2024,
    abstract = {The dataset used in the paper is a multi-view clustering dataset, which contains 6 views of 30000 samples each. The dataset is used to evaluate the performance of the proposed multi-view clustering algorithm.},
    author = {Tat-Seng Chua and Jinhui Tang and Richang Hong and Haojie Li and Zhiping Luo and Yan-Tao Zheng},
    doi = {10.57702/85y9yozb},
    institution = {No Organization},
    keyword = {'Dataset', 'Deep Learning', 'Image Classification', 'Image Retrieval', 'Large Scale Images', 'Large-Scale Dataset', 'Multimodal Search', 'NUS-WIDE', 'Object Detection', 'Semantic Search', 'Visual Search', 'Web Image', 'domain adaptation', 'image classification', 'image retrieval', 'k-means', 'manifold learning', 'multi-label', 'multi-view clustering', 'multi-view learning', 'object detection', 'semantic labeling', 'text retrieval', 'zero-shot learning'},
    month = {nov},
    publisher = {TIB},
    title = {NUS-WIDE},
    url = {https://service.tib.eu/ldmservice/dataset/nus-wide},
    year = {2024}
}