Before revision:  problems arise . Embedding models can be quite fast but perform poorly due to the lack of interaction across graphswhile matching models involve this for much better performance but satisfy far more on time consumption . Similar to the process of large biological molecular identification ,
After revision:  problems arise . Embedding models such as GCN-Mean and GCN-Max, which directly map graphs to respective feature vectors, run faster but the performance is usually poor due to the lack of interaction across graphswhile matching models involve this for much better performance but satisfy far more on time consumption . Similar to the process of large biological molecular identification ,