Document Usage Parameter for Search Relevance Ranking
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Solution Overview
Problem
Current ranking functions for documents in search engines do not effectively utilize actual document usage data to improve search results, leading to suboptimal relevance ranking.
Innovation Solution
A ranking function that incorporates query-independent components, including a document usage parameter based on actual usage data stored on a web server, to calculate document relevance scores, which are then used to rank documents in descending order of relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ranking functions are used without document usage data, then the ranking system is simpler and faster to compute, but the relevance accuracy of search results deteriorates
Solution Approach 1:
The patent pre-calculates and stores document usage statistics (view counts, download counts, etc.) in a usage database before search queries are processed. This preliminary action allows the ranking function to quickly retrieve pre-computed usage data without performing complex real-time calculations, thereby improving relevance accuracy while minimizing computational complexity during actual search operations
Solution Approach 2:
The patent introduces a usage database as an intermediary component between the search engine and documents. This database stores pre-computed usage statistics and provides them to the ranking function, acting as a mediator that supplies relevance information without requiring the search engine to directly analyze usage patterns, thus simplifying the overall system architecture while improving accuracy
2Measurement precision
If document usage data is collected and stored for all documents, then the relevance ranking improves, but the data storage requirements and processing overhead increase
Solution Approach 1:
The patent extracts only the most relevant usage statistics (such as view counts, download counts, and other key interaction metrics) from the complete document usage data. By selecting and storing only these essential metrics in the usage database, the system achieves improved ranking precision while minimizing the volume of stored data, avoiding the need to retain all possible usage information
3Measurement precision
If real-time usage data is processed for every search query, then the most current relevance information is obtained, but the computational time and resources increase significantly
Solution Approach 1:
The patent pre-computes document usage statistics and stores them in a usage database before search queries are executed. During actual search operations, the ranking function simply retrieves these pre-computed values without performing complex real-time calculations. This approach maintains high relevance accuracy by using up-to-date usage data while significantly reducing computational time and resource requirements during search processing
Data Source
AI summary
Methods of providing a document relevance score to a document on a network are disclosed. Computer readable medium having stored thereon computer-executable instructions for performing a method of providing a document relevance score to a document on a network are also disclosed. Further, computing systems containing at least one application module, wherein the at least one application module comprises application code for performing methods of providing a document relevance score to a document on a network are disclosed.