Partial Series Detection Apparatus Using Difference Score Accumulation
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Solution Overview
Problem
Existing detection apparatuses face challenges in accurately calculating the similarity between a partial series and a search pattern, particularly when using hidden Markov models, as the accumulative score varies with the number of parameters, making it difficult to represent similarity effectively.
Innovation Solution
A detection apparatus is designed with a local score acquirer, difference score calculator, and accumulative score calculator to determine similarity by subtracting a threshold from local scores and accumulating difference scores, allowing for comparison with a reference value to determine partial series similarity to a search pattern.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the accumulative score is calculated by accumulating local scores for each parameter in the partial series, then the similarity calculation becomes simple, but the accumulative score varies depending on the number of parameters making it difficult to represent similarity accurately
Solution Approach 1:
The patent changes the parameter representation by transforming local scores into difference scores through subtraction of a threshold value. This parameter transformation allows the accumulative score to represent similarity deviations from a baseline, making the measure independent of the number of parameters while maintaining calculation simplicity. The difference score formulation converts absolute score accumulation into relative deviation accumulation, resolving the contradiction between simplicity and accuracy.
2Quantity of substance
If the number of parameters in the partial series increases, then more comprehensive information is captured, but the absolute value of the accumulative score becomes larger reducing detection accuracy
Solution Approach 1:
The patent applies parameter change by introducing difference scores that represent deviations from a threshold rather than absolute scores. This transformation ensures that the accumulative score reflects the degree of similarity deviation regardless of the number of parameters accumulated. The threshold-based difference score formulation normalizes the contribution of each parameter, preventing the accumulative score from simply scaling with parameter count while maintaining comprehensive information capture.
Data Source
AI summary
According to an embodiment, a detection apparatus detects a partial series similar to a search pattern from a parameter series including a sequence of parameters. The apparatus includes a local score acquirer, a difference score calculator, an accumulative score calculator, and a determiner. The local score acquirer is configured to acquire a local score representing a likelihood of the parameter in the search pattern for each of the parameters. The difference score calculator is configured to calculate a difference score by subtracting a threshold from the local score for each of the parameters. The accumulative score calculator is configured to calculate an accumulative score by accumulating the difference scores. The determiner is configured to compare the accumulative score with a reference value in size to determine whether the partial series is similar to the search pattern.