User Query Mining for Website Structure Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing web mining techniques primarily focus on enhancing website search and do not effectively utilize user query data to improve website content and structure, missing opportunities to optimize user experience and website quality.
Innovation Solution
A model that classifies user queries and documents based on website usage data to identify new anchor text, content, and links, facilitating the enhancement of website structure and content by analyzing navigational patterns and query types, such as successful and unsuccessful queries, to improve user intuition and content relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing web mining techniques focus on enhancing website search, then search functionality is improved, but website content and structure optimization is neglected
Solution Approach 1:
The patent extends web mining techniques to serve multiple functions: not only enhancing search functionality but also optimizing website content and structure. The system analyzes user query data to generate suggestions for both search improvement and content/structure enhancement, making the mining process universally applicable to multiple website optimization goals.
Solution Approach 2:
The patent segments user queries into different categories (successful queries, unsuccessful queries, navigational queries) and applies different analysis methods to each segment. This segmentation allows the system to extract specific insights for search enhancement from one segment while extracting insights for content and structure optimization from other segments, resolving the contradiction between focused search improvement and broader website optimization.
2Measurement precision
If user query data is analyzed only for search enhancement, then search accuracy is improved, but opportunities for content and structure improvement are lost
Solution Approach 1:
The patent extracts different types of valuable information from user query data by categorizing queries into distinct types. Successful queries are extracted to identify effective search terms and content, while unsuccessful queries are extracted to identify gaps in website content and structure. This extraction process prevents loss of optimization opportunities while maintaining search accuracy improvements.
Solution Approach 2:
The patent adds another dimension to query analysis by not only analyzing what users search for (search accuracy dimension) but also how they navigate and what they fail to find (content and structure dimension). This dimensional expansion allows simultaneous improvement of search accuracy and identification of content/structure optimization opportunities from the same query data.
3Productivity
If comprehensive query analysis is performed to identify new content and links, then website quality is improved, but processing complexity increases
Solution Approach 1:
The patent applies partial action by focusing analysis on specific query types that provide the most value for content and structure optimization, such as unsuccessful queries and navigational queries. Rather than analyzing every aspect of all queries equally, the system selectively processes relevant segments, reducing processing complexity while maintaining website quality improvement.
Solution Approach 2:
The patent applies local quality by tailoring the analysis approach to different query types and website sections. Different classification rules and analysis methods are applied to different categories of queries (successful, unsuccessful, navigational), allowing the system to optimize processing efficiency for each local context while achieving comprehensive website quality improvement.
Data Source
AI summary
Methods and apparatus are described for mining user queries found within the access logs of a website and for relating this information to the website's overall usage, structure, and content. Such techniques may be used to discover valuable information to improve the quality of the website, allowing the website to become more intuitive and adequate for the needs of its users.