Tensor Counter for Visual Programming Language Behavior Tracking
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Solution Overview
Problem
Traditional graphical user interface (GUI) development toolkits are inadequate for creating visual programming languages (VPLs) as they do not support syntactic and semantic specifications, making it difficult and time-consuming to implement rules across multiple dimensions, requiring multiple counters for each attribute, leading to inefficient tracking of member behavior across various situations.
Innovation Solution
A processor-implemented method using a tensor counter within a visual programming application program to track member behavior across multiple dimensions, allowing for efficient specification and implementation by eliminating the need for separate counters for each combination of dimensions, reducing storage requirements and enabling fast computational processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional GUI development toolkits are used to create visual programming languages, then the interface can be designed, but it cannot support syntactic and semantic specifications making rule implementation difficult and time-consuming
Solution Approach 1:
The patent introduces a specialized visual programming environment as an intermediary system that bridges the gap between traditional GUI toolkits and the requirements for syntactic and semantic specification. This environment provides visual blocks that can be assembled to create rules, automatically handling the complex specification tasks that would otherwise require extensive manual programming work.
Solution Approach 2:
The patent replaces traditional mechanical programming approaches with a visual block-based system. Instead of writing code manually and dealing with syntax errors, users assemble pre-defined visual blocks that represent programming constructs. This substitution of the programming mechanism dramatically reduces implementation time while maintaining full syntactic and semantic specification capabilities.
2Measurement precision
If multiple counters are used to track member behavior across different dimensions and situations, then tracking accuracy is improved, but device complexity and storage requirements increase
Solution Approach 1:
The patent merges multiple separate counters into a single unified counter structure that can handle multiple dimensions and situations simultaneously. Instead of maintaining separate counters for different locations, time periods, and member attributes, the system combines these into one counter that processes all dimensions through a unified rule evaluation mechanism, reducing complexity while preserving tracking accuracy.
Solution Approach 2:
The patent creates a universal counter system that serves multiple functions: tracking member behavior across different locations, time periods, and situations all through the same counter structure. The counter is designed to be multi-functional, handling various tracking scenarios through configurable parameters rather than requiring separate dedicated counters for each function.
3Measurement precision
If separate counters are created for each combination of dimensions, then specific tracking requirements are met, but storage requirements and computational processing time increase
Solution Approach 1:
The patent merges the storage requirements for multiple dimension combinations into a single compact counter structure. Instead of allocating separate storage spaces for each dimension combination, the system uses a unified storage mechanism that efficiently organizes data across all dimensions, significantly reducing the total storage quantity needed while maintaining precise tracking capabilities.
Solution Approach 2:
The patent changes the parameters of the counter system to enable efficient storage and processing. By modifying how the counter handles dimension combinations - using configurable parameters and a unified evaluation approach - the system achieves precise tracking with reduced storage requirements and faster computational processing compared to traditional separate counter approaches.
Data Source
AI summary
A method of triggering an action by collectively tracking a behavior of a member across a plurality of dimensions is provided. The method includes obtaining, an action rule that specifies the action when the member performs the behavior in the plurality of dimensions, specifying a tensor counter that is a data structure to track the behavior based on the action rule, comprising a first data object storing name of behavior and a second data object comprising a plurality of keys and a plurality of values, determining the name and an updated value of the behavior, and a dimension associated with the behavior, modifying a value associated with the key to track the behavior of member in the dimension, updating the tensor counter to collectively track the behavior of member across the dimensions, and triggering the action to the member when the behavior of member matches the action rule.