Replication Data for: A degree-based block model and a local expansion optimization algorithm for anti-community detection  in networks
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'These dataset are the Replication Data for  A degree-based block model and a local expansion optimization algorithm for anti-community detection in networks, which is published in PLOS ONE with DOI: 10.1371/journal.pone.0195226.These dataset included synthetic and real-world networks, executable codes for benchmark DBM-Net, and proposed algorithms LEOA.' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Anti-community detection"]} <|eot_id|>
 Here is the Description of a dataset. Description:'These dataset are the Replication Data for  A degree-based block model and a local expansion optimization algorithm for anti-community detection in networks, which is published in PLOS ONE with DOI: 10.1371/journal.pone.0195226.These dataset included synthetic and real-world networks, executable codes for benchmark DBM-Net, and proposed algorithms LEOA.' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
These dataset are the Replication Data for  A degree-based block model and a local expansion optimization algorithm for anti-community detection in networks, which is published in PLOS ONE with DOI: 10.1371/journal.pone.0195226.These dataset included synthetic and real-world networks, executable codes for benchmark DBM-Net, and proposed algorithms LEOA.
Anti-community detection