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 , where we first maps the whole molecular to molecular groups and then identify them based on the "abstracted smaller molecular", the feature aggregation across two whole graphs is always redundant, especially when the number of nodes is large.
After 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 where the whole molecular to molecular groups and then identify them based on the "abstracted smaller molecular", the feature aggregation across two whole graphs is always redundant, especially when the number of nodes is large.