Also, let subsets: T pr in, T pr out, T p in and T p out, which refer to interconnections that load and exit product node pr and process unit p let f t be the flowrate (variable) of interconnection t the operation capacity of each process p is denoted by flowrates of interconnections, ∑ t ∈ T p in F t, s e, that load the process finally, let Y p be the known mass conversion rate output mass flowrate input mass flowrate of process p. Let the set of chemicals (product nodes) and paths (process units) of value chain: PR = be the seasons of biorefinery operation. The BBR ( Kokossis et al., 2015) is properly adjusted to the needs of this work and consists of three building blocks – product nodes, process units and interconnections (arcs) – to transform the unclear value chain into a representation, which is similar to a superstructure that translates arcs into chemicals flows. Kokossis, in Computer Aided Chemical Engineering, 2016 2.1 Value chain representation Nohup python run_pubmed.py -dataset tencent > running_asgcn.Konstantinos A. Nohup sh run_gae.sh pubmed > log_run_gae_pubmed.txt 2>&1 & Nohup sh run_gae.sh citeseer > log_run_gae_citeseer.txt 2>&1 & Nohup sh run_gae.sh cora > log_run_gae_cora.txt 2>&1 & Nohup sh run_gae.sh tencent > log_run_gae_tencent.txt 2>&1 & Nohup sh run_graphsage.sh pubmed > log_run_graphsage_pubmed.txt 2>&1 & Nohup sh run_graphsage.sh citeseer > log_run_graphsage_citeseer.txt 2>&1 & Nohup sh run_graphsage.sh cora > log_run_graphsage_cora.txt 2>&1 & Nohup sh run_graphsage.sh tencent > log_run_graphsage_tencent.txt 2>&1 & Nohup sh run_gcn.sh pubmed > log_run_gcn_pubmed.txt 2>&1 & Nohup sh run_gcn.sh citeseer > log_run_gcn_citeseer.txt 2>&1 & Nohup sh run_gcn.sh cora > log_run_gcn_cora.txt 2>&1 & Nohup sh run_gcn.sh tencent > log_run_gcn_tencent.txt 2>&1 & Nohup sh run_node2vec.sh pubmed > log_run_node2vec_pubmed.txt 2>&1 & Nohup sh run_node2vec.sh citeseer > log_run_node2vec_citeseer.txt 2>&1 & Nohup sh run_node2vec.sh cora > log_run_node2vec_cora.txt 2>&1 & Nohup sh run_node2vec.sh tencent > log_run_node2vec_tencent.txt 2>&1 & Nohup sh run_abcgraph_mlp.sh pubmed > log_run_abcgraph_mlp_pubmed.txt 2>&1 & Nohup sh run_abcgraph_mlp.sh citeseer > log_run_abcgraph_mlp_citeseer.txt 2>&1 & ![]() Nohup sh run_abcgraph_mlp.sh cora > log_run_abcgraph_mlp_cora.txt 2>&1 & Nohup sh run_abcgraph_mlp.sh tencent > log_run_abcgraph_mlp_tencent.txt 2>&1 & Nohup sh run_abcgraph_adv.sh pubmed > log_run_abcgraph_adv_pubmed.txt 2>&1 & Nohup sh run_abcgraph_adv.sh citeseer > log_run_abcgraph_adv_citeseer.txt 2>&1 & Nohup sh run_abcgraph_adv.sh cora > log_run_abcgraph_adv_cora.txt 2>&1 & Nohup sh run_abcgraph_adv.sh tencent > log_run_abcgraph_adv_tencent.txt 2>&1 & From the other datasets, we can see that our model's performance is better than the GAE model. To apply GAE to the large-scale graph data is another research topic, so we don't report the result in the "Tencent" dataset. N/A (*): For the GAE model, the code of the original GAE paper can not simply applied to the large-scale bipartite graph due to the memory constrain. ![]() Only Linux (*): For the Node2Vec model, its binary file is only ELF 64-bit LSB executable, x86-64, for GNU/Linux.
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