MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection
Authors: Ling Huang, Hong-Yang Chao, Quangqiang Xie107-114
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments are conducted on five real-world networks. Comparison results with twelve existing approaches confirm the effectiveness of the proposed method. |
| Researcher Affiliation | Academia | 1School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China 2Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, China 3School of Computer, Guangdong University of Technology, Guangzhou, China |
| Pseudocode | Yes | Algorithm 1 Mu Mod |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of its source code. |
| Open Datasets | Yes | Polbooks1: A network of books about US politics... Email-Eu-core2: An email network... Polblogs1: A network of hyperlinks... Cora3: A citation network... DBLP4: A subset of the DBLP data. with corresponding footnotes providing URLs: 1http://www-personal.umich.edu/ mejn/netdata/ 2http://snap.stanford.edu/data/ 3http://linqs.cs.umd.edu/projects/projects/lbc/ 4http://dblp.uni-trier.de/ |
| Dataset Splits | No | The paper mentions 'testing datasets' and evaluates performance measures on them, but it does not provide specific details on how the datasets were split into training, validation, and test sets (e.g., percentages, sample counts, or cross-validation setup). |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper mentions 'MATLAB' in reference to a generalized Louvain method, but it does not provide specific version numbers for any software dependencies (e.g., programming languages, libraries, frameworks) used for the authors' own implementation or experiments. |
| Experiment Setup | Yes | In particular, when setting γ as 1 and 1.25, the best results can be obtained, which coincides with the studies in the previous work (Newman 2006; Mucha et al. 2010). Following (Mucha et al. 2010), we will set the resolution parameter γ as 1 in the following experiments. |