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该代码分两个部分,第一部分需要python运行的Node2vec部分,第二部分为matlab运行的算法主题部分, 其中Node2vec部分会将生成的先验信息保存到txt中,matlab运行时会读取该部分信息作为指导。

注意事项,

  1. 本机运行环境为matlab r2016a,改代码需要适配对应版本globaloptim包(将其替换matlab\toolbox中的重名包)
  2. 请自行调整python中与matlab中的文件保存路径(matlab文件路径在运行文件和create_populationLS中)
  3. 示例代码中仅采用NMI指标(文件中有ARI),可根据输出和label格式自行添加及设计不同评估指标

运行:

  1. 运行python文件获取先验信息,github上有不同实现的node2vec代码,请自行下载
  2. 运行matlab中 run_MLMaOPmainsyn.m 更换数据集请 注释\取消注释 不同的代码块
  3. 运行前需要在matlab左侧目录中把True及其子文件引入加入路径,matlab才能搜索到数据集

注1:snd数据集为样例,python中间结果已经拷贝到example_pre_extracted_prior_information中,直接运行即可,不需要运行python,其余数据集须调整路径

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