Search Result Redistributor Using Natural Distribution Index
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Solution Overview
Problem
Conventional search systems face challenges in presenting the best search results among a vast number of potential results, leading to difficulties in identifying relevant information due to scoring inaccuracies and presentation bias.
Innovation Solution
The technology redistributes ranked search results based on a natural distribution index, which maps search query terms to search result attributes and represents interactions with these attributes, thereby minimizing the gap between the ranked results and the natural distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search systems rank search results based on scoring algorithms, then search results are provided in a standardized format, but scoring inaccuracies and presentation bias make it difficult for users to identify relevant information
Solution Approach 1:
The patent introduces a blender as an intermediary component that sits between the conventional ranking system and the user. The blender receives ranked search results and redistributes them according to a natural distribution derived from historical user interactions. This intermediary layer corrects the biases and inaccuracies of the original scoring algorithm without requiring changes to the core ranking system, thereby improving relevance identification while maintaining system stability.
Solution Approach 2:
The system utilizes feedback from historical user interactions with search results to construct a natural distribution. By analyzing patterns in how users actually interact with search results (clicks, views, selections), the system creates a feedback loop that informs the redistribution process. This feedback mechanism allows the system to continuously improve its ability to identify relevant information by learning from actual user behavior rather than relying solely on theoretical scoring algorithms.
2Quantity of substance
If search systems present a vast number of potential search results, then comprehensive coverage is achieved, but users face difficulties in identifying relevant information among the large volume of results
Solution Approach 1:
The patent applies local quality by redistributing search results based on their specific attributes and historical interaction patterns. Instead of treating all search results uniformly, the system analyzes individual result characteristics and their performance in historical contexts, then positions them in the results list according to their local quality metrics. This allows highly relevant results to be prominently displayed while maintaining comprehensive coverage of the search topic.
3Productivity
If conventional ranking algorithms are used to order search results, then processing efficiency is maintained, but presentation bias reduces the accuracy of result presentation
Solution Approach 1:
The system performs preliminary action by pre-computing the natural distribution from historical interaction data and storing it for efficient retrieval. This pre-processing step allows the blender to quickly redistribute search results during query processing without performing complex calculations in real-time. The preliminary computation of interaction patterns enables the system to maintain high processing efficiency while applying bias-correction redistributions.
Data Source
AI summary
A search engine is provided that generates search results proportional to a natural distribution. Search results identified and ranked by the search engine for a search query are redistributed so that a fixed number of top ranked search results include search result attributes proportional to the natural distribution, as determined from interaction tracking of prior search results. A natural distribution index mapping prior search queries to search result attributes and a proportional representation of interactions with the search result attributes is generated. The natural distribution is determined from the proportional representation of interactions. The search engine redistributes the fixed number of top ranked search results by minimizing a gap between the ranked set of search results for the search query and the natural distribution.