Search Term Popularity Peak Analysis
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Solution Overview
Problem
Conventional search systems face challenges in providing accurate and relevant related search terms due to limitations in concept hierarchy, synonyms, and related meanings, often resulting in non-relevant results and unsatisfactory user experience.
Innovation Solution
A method and system that analyze search logs to extract daily search frequencies, compare peaks in search term distributions, and filter out irrelevant candidate terms to identify related terms with rapidly increasing popularity based on shared peaks and relevance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to search for related terms (concept hierarchy, synonyms, related meanings), then the search system can provide related search queries, but the accuracy and relevance of the results deteriorate due to extracting non-related terms and failing to satisfy user demand for high-quality results
Solution Approach 1:
The patent changes the parameter for identifying related terms from static conceptual relationships (hierarchy, synonyms) to dynamic temporal patterns (search frequency peaks over time). By analyzing when search terms reach peak popularity and comparing these temporal patterns, the system identifies related terms based on their co-occurrence in peak periods, significantly improving accuracy and relevance of search results
Solution Approach 2:
The patent replaces the conventional mechanical approach of using predefined concept hierarchies and synonym databases with a data-driven temporal pattern analysis mechanism. Instead of relying on static lexical relationships, the system uses search log data to detect and compare temporal peaks in search frequency, substituting the mechanical concept-matching system with a statistical pattern recognition approach
2Productivity
If the system provides related search queries based on conventional methods, then users can perform searching with related terms, but the timeliness and popularity awareness of the results deteriorate
Solution Approach 1:
The system performs preliminary analysis of search logs to identify and store temporal peak patterns of search terms before users make their queries. By pre-processing and indexing this temporal data, the system can quickly match current search queries against stored peak patterns to rapidly identify related terms with rising popularity, enabling fast and timely search results
Data Source
AI summary
A method and system for searching for a related term having rapidly increasing popularity is provided. The method includes: analyzing a search log and extracting a daily search frequency for each search term; comparing peaks of the daily search frequency, extracted for each search term in a predetermined period; and analyzing relevance between candidate search terms in which the peaks have occurred together in the predetermined period as a result of the comparison and filtering out a candidate search term having no relevance.