Webpage Decision Tree Optimization via Semantic Grouping

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Solution Overview

Problem

Existing webpage optimization mechanisms fail to effectively minimize the average number of clicks (ANC) in decision tree structures and do not utilize semantic optimization techniques, leading to inefficient navigation and content exploration.

Innovation Solution

A computing system that incorporates decision tree analysis (DTA) circuitry to receive historical usage data and natural language processing (NLP) circuitry to generate semantic grouping data, optimizing the decision tree structure to reduce the ANC value, thereby generating a more efficient webpage decision tree structure.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If traditional webpage optimization mechanisms are used, then implementation is simple, but the average number of clicks (ANC) cannot be effectively minimized

Engineering Contradiction:

Improveaverage number of clicksVSAvoidoptimization system complexity

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The optimization system is segmented into distinct functional modules: decision tree analysis circuitry for structural analysis, natural language processing circuitry for semantic understanding, and decision tree optimization circuitry for restructuring. This segmentation allows each module to specialize in specific tasks while working together to minimize ANC effectively.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces semantic grouping data as an intermediary element that bridges historical usage data and decision tree structure optimization. This semantic intermediary enables the system to understand the meaning and relationships between webpage nodes, facilitating more intelligent optimization decisions that reduce click paths.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If semantic optimization techniques are not utilized, then processing requirements are lower, but navigation efficiency and content exploration are impaired

Engineering Contradiction:

Improvenavigation efficiencyVSAvoidcomputational processing

Core Design Contradiction:

Ease of operationVSQuantity of substance

Solution Approach 1:

The system performs preliminary semantic analysis and grouping of webpage nodes before the actual optimization process. By pre-processing the data to extract semantic meanings and relationships, the system reduces the computational burden during optimization while improving navigation efficiency through better-informed restructuring decisions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces traditional mechanical optimization approaches (based solely on click count statistics) with semantic-based optimization using natural language processing. This substitution enables the system to understand the contextual meaning of webpage nodes, leading to more intuitive and efficient navigation structures that reduce the average number of clicks.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If historical usage data is not analyzed, then data processing requirements are reduced, but the accuracy of optimization decisions deteriorates

Engineering Contradiction:

Improveoptimization decision accuracyVSAvoidhistorical data processing

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The system transforms historical usage data from raw click counts into meaningful parameters including frequency of access, temporal patterns, and semantic relationships. This parameter transformation enables more accurate optimization decisions by considering multiple dimensions of user behavior rather than simple aggregate statistics.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements a feedback mechanism where historical usage data continuously informs optimization decisions. The system analyzes past user interactions, identifies patterns in navigation behavior, and uses this feedback to iteratively improve the decision tree structure, thereby increasing optimization accuracy over time while managing data processing requirements through efficient feedback loops.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11599596B2Systems and methods for optimizing a webpage based on historical and semantic optimization of webpage decision tree structures

Publication Date: 2023.03.07 BYTEDANCE INC

AI summary

Computing systems, computing apparatuses, computing methods, and computer program products are disclosed for optimizing a webpage. An example computing method includes determining a first average number of clicks (ANC) value for a first set of webpage nodes based on first webpage decision tree data and historical usage data. The example computing method further includes generating semantic grouping data for the first set of webpage nodes based on the first webpage decision tree data and webpage node description data. The example computing method further includes determining a second ANC value based on the first set of webpage nodes. The example computing method further includes generating, based on the second ANC value and the semantic grouping data, second webpage decision tree data.