Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (SRL). The hybrid kernel consists of two individual convolution kernels: a Path kernel, which captures predicate-argument link features, and a Constituent Structure kernel, which captures the syntactic structure features of arguments. Evaluation on the datasets of CoNLL-2005 SRL shared task shows that the novel hybrid convolution tree kernel out-performs the previous tree kernels.  also combine our new hybrid tree kernel based method with the standard rich flat feature based method. The experimental results show that the combinational method can get better performance than each of them individually.
['Wanxiang Che', 'Min Zhang', 'Ting Liu', 'Sheng Li']
I am writing a research paper on a idea A Hybrid Convolution Tree Kernel for Semantic Role Labeling
[{"from": "human", "value": "I am writing a research paper on a idea A Hybrid Convolution Tree Kernel for Semantic Role Labeling"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (SRL). The hybrid kernel consists of two individual convolution kernels: a Path kernel, which captures predicate-argument link features, and a Constituent Structure kernel, which captures the syntactic structure features of arguments. Evaluation on the datasets of CoNLL-2005 SRL shared task shows that the novel hybrid convolution tree kernel out-performs the previous tree kernels.  also combine our new hybrid tree kernel based method with the standard rich flat feature based method. The experimental results show that the combinational method can get better performance than each of them individually."}]