Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of pattern directly from the data, our approach extracts the temporal structure of the time-series data by learning Markovian models, and then uses ll established methods to efficiently mine a wide variety of patterns from the topology graph of the learned models.  consolidate the approach by explaining the use of some ll-known Markovian models on mining several kinds of patterns.  then present a novel high-order hidden Markov model, the variable-length hidden Markov model (VLHMM), which combines the advantages of ll- known Markovian models and has the superiority in both efficiency and accuracy. Therefore, it can mine a much wider variety of patterns than each of prior Markovian models.  demonstrate the por of VLHMM by mining four kinds of interesting patterns from 3D motion capture data, which is typical for the high-dimensionality and complex dynamics.
['Yi Wang', 'Lizhu Zhou', 'Jianhua Feng', 'Jianyong Wang', 'Zhi-Qiang Liu']
I am writing a research paper on a idea Mining Complex Time-Series Data by Learning Markovian Models
[{"from": "human", "value": "I am writing a research paper on a idea Mining Complex Time-Series Data by Learning Markovian Models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of pattern directly from the data, our approach extracts the temporal structure of the time-series data by learning Markovian models, and then uses ll established methods to efficiently mine a wide variety of patterns from the topology graph of the learned models.  consolidate the approach by explaining the use of some ll-known Markovian models on mining several kinds of patterns.  then present a novel high-order hidden Markov model, the variable-length hidden Markov model (VLHMM), which combines the advantages of ll- known Markovian models and has the superiority in both efficiency and accuracy. Therefore, it can mine a much wider variety of patterns than each of prior Markovian models.  demonstrate the por of VLHMM by mining four kinds of interesting patterns from 3D motion capture data, which is typical for the high-dimensionality and complex dynamics."}]