Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In recent years, many algorithms have been proposed to discover frequent itemsets over uncertian databases or mine ighted-based frequent itemsets from precisely binary databases. None of the above algorithms have been, hover, designed to discover interesting patterns by considering both ight and data uncertainty constraints. , a novel knowledge called high expected ighted itemsets (HEWIs) is designed to reveal more useful and meaningful information by considering both the ight and existential probability constraints over an uncertain database. A two-phase HEWI-UTP algorithm is developed to overestimate the high upper-bound expected-ighted itemsets (HUBEWIs) based on the developed high upper-bound expected ighted downward closure property, which can be used to reduce the search space for discovering HEWIs. An extensive experimental study carried on several real-life and synthetic datasets shows the performance of the proposed algorithm.
['Jerry Chun-Wei Lin', 'Wensheng Gan', 'Tzung-Pei Hong', 'Vincent S. Tseng']
I am writing a research paper on a idea Hewin: High expected weighted itemset mining in uncertain databases
[{"from": "human", "value": "I am writing a research paper on a idea Hewin: High expected weighted itemset mining in uncertain databases"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In recent years, many algorithms have been proposed to discover frequent itemsets over uncertian databases or mine ighted-based frequent itemsets from precisely binary databases. None of the above algorithms have been, hover, designed to discover interesting patterns by considering both ight and data uncertainty constraints. , a novel knowledge called high expected ighted itemsets (HEWIs) is designed to reveal more useful and meaningful information by considering both the ight and existential probability constraints over an uncertain database. A two-phase HEWI-UTP algorithm is developed to overestimate the high upper-bound expected-ighted itemsets (HUBEWIs) based on the developed high upper-bound expected ighted downward closure property, which can be used to reduce the search space for discovering HEWIs. An extensive experimental study carried on several real-life and synthetic datasets shows the performance of the proposed algorithm."}]