A tree-structured data matching method is summarized in this section based on our previous research [35]–[38]. To identify the parts of the two trees that most conceptually correspond, a maximum conceptual similarity tree mapping [38] is constructed.When constructing the mapping, tree structures, node concepts, and node weights are all taken into consideration.It should be noted that in contrasting application scenarios, the requirements to match two trees are different. For example, when comparing two trees, the weights of both trees should beconsidered. Another example is matching a subtree to a target tree to find out whether the target tree includes the subtree, where the weights of the subtree should mainly be weighted. Therefore, the matching method should consider the two types of matching situations, respectively. In the former situation, the matching is called symmetric matching, while the latter is called asymmetric matching. The maximum conceptual similarity tree mapping can be constructed during the computation of the conceptual similarity between two trees. The conceptual similarity also has two types, symmetric and asymmetric, depending on the matching types. They are denoted as scT sym and scT asym when the matching type needs to be specified.
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