Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically ad- dresses the problems of indexing, clustering, classification, summarization, and anomaly detection. They present many ways for describing and comparing time series, but they fo- cus on their values.  concentrates on a new as- pect - that of describing oscillation patterns. It presents a technique for time series similarity search, based on multi- ple temporal scales, defining a descriptor that uses the an- gular coefficients from a linear segmentation of the curve that represents the evolution of the analyzed series. Prelim- inary experiments with real datasets shod that our ap- proach correctly characterizes the oscillation of time series.
['Leonardo Elias Mariote', 'Claudia Bauzer Medeiros', 'Ricardo da Silva Torres']
I am writing a research paper on a idea Diagnosing Similarity of Oscillation Trends in Time Series
[{"from": "human", "value": "I am writing a research paper on a idea Diagnosing Similarity of Oscillation Trends in Time Series"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically ad- dresses the problems of indexing, clustering, classification, summarization, and anomaly detection. They present many ways for describing and comparing time series, but they fo- cus on their values.  concentrates on a new as- pect - that of describing oscillation patterns. It presents a technique for time series similarity search, based on multi- ple temporal scales, defining a descriptor that uses the an- gular coefficients from a linear segmentation of the curve that represents the evolution of the analyzed series. Prelim- inary experiments with real datasets shod that our ap- proach correctly characterizes the oscillation of time series."}]