Weighted Suffix Tree Data Analysis Method
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Solution Overview
Problem
Existing data analysis methods in social network and astronomical observation domains generate extensive, complex data that is difficult to mine effectively, with limited utilization of influence paths and observation patterns.
Innovation Solution
A method utilizing a weighted suffix tree to classify and merge nodes, reducing computational complexity by simplifying data representation while maintaining stored information, allowing for flexible data analysis and output for further mining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If nodes in the weighted suffix tree are classified and merged according to group information, then the data representation is simplified and computational complexity is reduced, but the information completeness may be compromised
Solution Approach 1:
The patent merges nodes in the weighted suffix tree that belong to the same group according to group information. This consolidation reduces the number of nodes and edges in the tree structure, thereby simplifying the data representation and reducing computational complexity for subsequent data analysis operations while preserving the essential information through the weighting mechanism.
Solution Approach 2:
The patent introduces group information as a new parameter to classify and organize nodes in the weighted suffix tree. By assigning group labels to nodes and using these groups as the basis for merging operations, the system transforms the raw node structure into a grouped structure that enables simplified representation while maintaining information integrity through the weight sets associated with each node.
2Quantity of substance
If extensive data is collected from social network influence paths and astronomical observation patterns, then the analysis coverage is improved, but the data mining difficulty increases
Solution Approach 1:
The patent segments the extensive data into structured sequences and builds a weighted suffix tree where data is organized into manageable nodes and edges. This segmentation transforms the raw extensive data into a hierarchical structure that can be systematically processed, reducing the difficulty of data mining while maintaining comprehensive coverage of the input data.
Solution Approach 2:
The weighted suffix tree acts as an intermediary data structure between the raw extensive data and the final analysis results. By introducing this intermediate representation with nodes, edges, and weight sets, the system facilitates easier data mining operations while preserving the comprehensive information from the original data sources.
Data Source
AI summary
A method for analyzing data utilizing a weighted suffix tree includes receiving at least one original data sequence. An original data sequence ID is assigned to the original data sequence, and the original data sequence includes an original datums. A weighted suffix tree is constructed according to the original datums of the original data sequence. The weighted suffix tree includes several nodes, and each node includes a weight set which is formed by the original data sequence ID. Group information for classifying the original datums into several groups is received. The nodes of the weighted suffix tree belonging to a same group are merged according to the group information. Data is analyzed according to the weighted suffix tree after being merged.