Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster in terms of computation time. Prediction performance is worse than the state-of-the-art isfeiler Lehman RDF kernel, but our kernel is a factor 10 faster to compute. Thus,  consider this kernel a very suitable baseline for learning from RDF data. Furthermore,  extend this kernel to handle RDF literals as bag-ofwords feature vectors, which increases performance in two of the four experiments.
['Gerben de Vries', 'Steven de Rooij']
I am writing a research paper on a idea A Fast and Simple Graph Kernel for RDF
[{"from": "human", "value": "I am writing a research paper on a idea A Fast and Simple Graph Kernel for RDF"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster in terms of computation time. Prediction performance is worse than the state-of-the-art isfeiler Lehman RDF kernel, but our kernel is a factor 10 faster to compute. Thus,  consider this kernel a very suitable baseline for learning from RDF data. Furthermore,  extend this kernel to handle RDF literals as bag-ofwords feature vectors, which increases performance in two of the four experiments."}]