Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data mining can be vied, in many instances, as the task of computing a representation of a theory of a model or a database, in particular by finding a set of maximally specific sentences satisfying some property.  prove some hardness results that rule out simple approaches to solving the problem.The  a priori  algorithm is an algorithm that has been successfully applied to many instances of the problem.  analyze this algorithm, and prove that is optimal when the maximally specific sentences are "small".  also point out its limitations. then present a new algorithm, the Dualize and Advance algorithm, and prove worst-case complexity bounds that are favorable in the general case. Our results use the concept of hypergraph transversals. Our analysis shows that the  a priori  algorithm can solve the problem of enumerating the transversals of a hypergraph, improving on previously known results in a special case. On the other hand, using results for the general case of the hypergraph transversal enumeration problem,  can show that the Dualize and Advance algorithm has worst-case running time that is sub-exponential to the output size (i.e., the number of maximally specific sentences). further show that the problem of finding maximally specific sentences is closely related to the problem of exact learning with membership queries studied in computational learning theory.
['Dimitrios Gunopulos', 'Roni Khardon', 'Heikki Mannila', 'Sanjeev Saluja', 'Hannu Toivonen', 'Ram Sewak Sharma']
I am writing a research paper on a idea Discovering all most specific sentences
[{"from": "human", "value": "I am writing a research paper on a idea Discovering all most specific sentences"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data mining can be vied, in many instances, as the task of computing a representation of a theory of a model or a database, in particular by finding a set of maximally specific sentences satisfying some property.  prove some hardness results that rule out simple approaches to solving the problem.The  a priori  algorithm is an algorithm that has been successfully applied to many instances of the problem.  analyze this algorithm, and prove that is optimal when the maximally specific sentences are \"small\".  also point out its limitations. then present a new algorithm, the Dualize and Advance algorithm, and prove worst-case complexity bounds that are favorable in the general case. Our results use the concept of hypergraph transversals. Our analysis shows that the  a priori  algorithm can solve the problem of enumerating the transversals of a hypergraph, improving on previously known results in a special case. On the other hand, using results for the general case of the hypergraph transversal enumeration problem,  can show that the Dualize and Advance algorithm has worst-case running time that is sub-exponential to the output size (i.e., the number of maximally specific sentences). further show that the problem of finding maximally specific sentences is closely related to the problem of exact learning with membership queries studied in computational learning theory."}]