Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The aim of this paper is to start a comparison beten recursive neural networks (RecNN) and kernel methods for structured data, specifically support vector regression (SVR) machine using a tree kernel, in the context of regression tasks for trees. Both the approaches can deal directly with a structured input representation and differ in the construction of the feature space from structured data.  present and discuss preliminary empirical results for specific regression tasks involving ll-known quantitative structure-activity and quantitative structure-property relationship (QSAR/QSPR) problems, where both the approaches are able to achieve state-of-the-art results.
['Alessio Micheli', 'Filippo Portera', 'Alessandro Sperduti']
I am writing a research paper on a idea A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains
[{"from": "human", "value": "I am writing a research paper on a idea A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The aim of this paper is to start a comparison beten recursive neural networks (RecNN) and kernel methods for structured data, specifically support vector regression (SVR) machine using a tree kernel, in the context of regression tasks for trees. Both the approaches can deal directly with a structured input representation and differ in the construction of the feature space from structured data.  present and discuss preliminary empirical results for specific regression tasks involving ll-known quantitative structure-activity and quantitative structure-property relationship (QSAR/QSPR) problems, where both the approaches are able to achieve state-of-the-art results."}]