Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In applications like sensor network monitoring and location-based services, due to limited network bandwidth and battery por, a system cannot always acquire accurate and fresh data from the external environment. To capture data errors in these environments, recent researches have proposed to model uncertainty as a probability distribution function (pdf), as ll as the notion of probabilistic queries, which provide statistical guarantees on ansr correctness. ,  present an entropy-based metric to quantify the degree of ambiguity of probabilistic query ansrs due to data uncertainty. Based on this metric,  develop a new method to improve the query ansr quality. The main idea of this method is to acquire (or probe) data from a selected set of sensing devices, in order to reduce data uncertainty and improve the quality of a query ansr. Given that a query is assigned a limited number of probing resources,  investigate how the quality of a query ansr can attain an optimal improvement. To improve the efficiency of our solution,  further present heuristics which achieve near-to-optimal quality improvement.  generalize our solution to handle multiple queries. An experimental simulation over a realistic dataset is performed to validate our approaches.
['Jinchuan Chen', 'Reynold Cheng']
I am writing a research paper on a idea Quality-Aware Probing of Uncertain Data with Resource Constraints
[{"from": "human", "value": "I am writing a research paper on a idea Quality-Aware Probing of Uncertain Data with Resource Constraints"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In applications like sensor network monitoring and location-based services, due to limited network bandwidth and battery por, a system cannot always acquire accurate and fresh data from the external environment. To capture data errors in these environments, recent researches have proposed to model uncertainty as a probability distribution function (pdf), as ll as the notion of probabilistic queries, which provide statistical guarantees on ansr correctness. ,  present an entropy-based metric to quantify the degree of ambiguity of probabilistic query ansrs due to data uncertainty. Based on this metric,  develop a new method to improve the query ansr quality. The main idea of this method is to acquire (or probe) data from a selected set of sensing devices, in order to reduce data uncertainty and improve the quality of a query ansr. Given that a query is assigned a limited number of probing resources,  investigate how the quality of a query ansr can attain an optimal improvement. To improve the efficiency of our solution,  further present heuristics which achieve near-to-optimal quality improvement.  generalize our solution to handle multiple queries. An experimental simulation over a realistic dataset is performed to validate our approaches."}]