Decrementing Sliding Walker Data Segmentation
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Solution Overview
Problem
Existing data segmentation techniques, such as the fixed-size walker method, can miss patterns that span segment boundaries, leading to incomplete pattern detection in large data sets.
Innovation Solution
A decrementing, sliding walker method is employed to segment data sets into all possible sizes and contents, allowing for thorough pattern identification by creating segments of varying sizes and contents, which are then analyzed for recurring patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed-size walker is used to segment data into contiguous segments, then the segmentation process is simple and efficient, but patterns that span segment boundaries are missed
Solution Approach 1:
The patent applies segmentation by dividing the data set into multiple segments of varying sizes using a walker that can be positioned at different locations. The walker creates segments that may overlap, ensuring that patterns spanning boundaries are captured within at least one segment. This resolves the contradiction by maintaining efficient segmentation while improving pattern detection completeness through strategic segment division.
Solution Approach 2:
The patent introduces a new dimension to the segmentation approach by allowing the walker to operate at multiple positions and create segments of different sizes rather than using a single fixed size. This multi-dimensional approach to segmentation ensures comprehensive pattern detection while maintaining processing efficiency.
2Measurement precision
If the data set is divided into many small segments to capture all patterns, then pattern detection accuracy improves, but the complexity of processing increases
Solution Approach 1:
The patent employs a dynamic walker approach where the walker size and position are adjusted based on the data characteristics and search requirements. This dynamic adaptation allows the system to achieve high pattern detection accuracy without consistently processing complex large segments, thereby reducing overall processing complexity while maintaining precision.
Solution Approach 2:
The patent changes the parameters of the walker (size, position, step) to optimize the segmentation strategy. By dynamically adjusting these parameters, the system achieves accurate pattern detection without unnecessarily increasing processing complexity, resolving the contradiction between precision and complexity.
Data Source
AI summary
A method for segmenting a data set is disclosed. The method consists of setting a maximum walker size and setting a walker size. Then, a first segment of data from the data set is obtained, wherein the first segment of data is the size of the walker. Then, a second segment of data from the data set is obtained, wherein the second segment of data is not greater than the maximum walker size.