Aligning Contrastive Multiple Clusterings with User Interests
Authors: Shan Zhang, Liangrui Ren, Jun Wang, Yanyu Xu, Carlotta Domeniconi, Guoxian Yu
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on benchmark datasets show that CMClusts can generate interpretable and high-quality clusterings, which reflect different user interests. We conduct experiments using real-world benchmark datasets, and compare CMClusts against representative and competitive multiple clustering methods. |
| Researcher Affiliation | Academia | Shan Zhang1 , Liangrui Ren1 , Jun Wang1 , Yanyu Xu1 , Carlotta Domeniconi2 , Guoxian Yu1 1School of Software, Shandong University, Jinan, China 2Department of Computer Science, George Mason University, VA, USA |
| Pseudocode | Yes | Algorithm 1 lists the procedure of CMClusts. |
| Open Source Code | Yes | The source code of CMClusts is available at https://www.sduidea.cn/codes.php?name=CMClusts. |
| Open Datasets | Yes | Seven benchmark datasets (ALOI [Geusebroek et al., 2005], Fruit [Yao et al., 2023], CMUFace [Ren et al., 2023b], COIL [Nayar, 1996], Cards [Yao et al., 2023], Web KB and Mice [Ren et al., 2023b]) are used to evaluate the performance of CMClusts and other baselines. These datasets have been widely used to validate multiple clustering methods [Bailey, 2018; Yu et al., 2024]. |
| Dataset Splits | No | No specific training/test/validation dataset splits are provided in the main text. The paper mentions: "More details are provided in the supplementary file." regarding datasets. |
| Hardware Specification | Yes | Additionally, all the methods are implemented in Py Torch 2.4 and tested on a server with NVIDIA L40 GPUs. |
| Software Dependencies | Yes | All the methods are implemented in Py Torch 2.4 and tested on a server with NVIDIA L40 GPUs. |
| Experiment Setup | No | No specific hyperparameter values or detailed training configurations are provided in the main text. The paper states: "And the α and β are hyperparameters. For a detailed analysis, please refer to the supplementary file." |