Real-Time Keyword Trend Detection via Adaptive Time Windows
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Internet search service providers struggle to detect keywords with rapidly increasing input numbers in real-time, leading to delayed recognition and ineffective response, as existing methods require a predetermined period to assess trends, resulting in missed opportunities for providing optimized search results.
Innovation Solution
A method and system that collect log data at regular intervals, estimate keyword input numbers, calculate estimated search numbers, and use criterion values to detect rapidly increased keywords in real-time, allowing for immediate identification and updating of keyword trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a predetermined period is used to measure click number trends, then measurement accuracy is improved, but detection speed deteriorates
Solution Approach 1:
The patent applies dynamics by making the measurement period adaptive rather than fixed. The system dynamically adjusts the time window for measuring click trends based on detected changes in search behavior. When rapid changes are detected, the system shortens the measurement period to enable faster detection, while maintaining sufficient data for accurate trend analysis. This resolves the contradiction by allowing the system to achieve both measurement accuracy and detection speed through adaptive period selection.
Solution Approach 2:
The patent implements preliminary action by continuously collecting and pre-processing click data in real-time before a complete trend analysis is needed. The system maintains a running record of click numbers and preliminary trend indicators, so when detection is required, the analysis can be performed immediately on pre-processed data rather than collecting data from scratch. This reduces detection delay while maintaining measurement accuracy.
2Loss of time
If real-time detection is implemented, then detection speed is improved, but measurement precision deteriorates
Solution Approach 1:
The system dynamically adjusts the measurement window size based on the detected rate of change. When search trends are stable, a longer measurement period is used to ensure accuracy. When rapid changes are detected, the system transitions to a shorter, real-time measurement window that prioritizes detection speed while using statistical methods to maintain sufficient precision for identifying significant trends.
Solution Approach 2:
The patent applies partial action by using a sliding window approach that processes only the most recent data points relevant to current trends rather than analyzing all historical data. This allows real-time detection with adequate precision by focusing computational resources on the most relevant recent data, achieving fast detection without sacrificing essential measurement accuracy.
3Measurement precision
If manual discernment of frequent terms is used, then detection accuracy is improved, but productivity deteriorates
Solution Approach 1:
The patent implements feedback by using automated algorithms that continuously analyze click data and provide real-time feedback on emerging trends. The system monitors detection results and adjusts its analysis parameters based on detected patterns, enabling both high accuracy and high productivity through automated iterative refinement rather than manual discernment.
Solution Approach 2:
The patent replaces the mechanical system of manual discernment with an automated computational system that uses algorithms to analyze click data, identify patterns, and detect emerging keywords. This substitution maintains or improves detection accuracy through systematic analysis while dramatically increasing productivity by eliminating manual processing limitations.
4Adaptability or versatility
If comprehensive keyword analysis is performed across all fields, then detection coverage is improved, but device complexity deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the comprehensive keyword analysis into field-specific or category-specific analysis modules. Each module handles a particular domain or topic area independently, allowing the system to maintain broad detection coverage across all fields while reducing overall system complexity through modular organization. Each segment can be optimized independently for its specific domain.
Data Source
AI summary
A method and a system of detecting a keyword whose input number is rapidly increased in real time which can estimate a search number at a future point in time by reflecting an input trend of the keyword in real time at a present point in time and can immediately detect the keyword whose input number is rapidly increased according to a criterion value calculated by the estimated search number. Specifically, the method and system of detecting a keyword whose input number is rapidly increased in real time which can estimate the search number for each keyword at the future point in time in real time and can immediately detect the keyword whose input number is rapidly increased according to a criterion value calculated by the estimated search number.