Search Result Summarization via Clustering and Interactive Refinement
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Solution Overview
Problem
Current search engines present ranked search results in an inefficient manner, leading to duplication and false positives when searching for specific image or video content, requiring users to manually scroll through numerous results to find the target, which is time-consuming and tedious.
Innovation Solution
A method and system that summarize search results by clustering and identifying dominant and distinctive features, allowing users to refine their queries interactively through a visual interface, such as similarity embedding, cluster, or tree views, and assisted by a chatbot for efficient search refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If search engines return all ranked search results, then completeness of search results is improved, but time consumption for manual review increases
Solution Approach 1:
The patent segments search results into multiple clusters based on similarity, organizing numerous results into grouped categories. This allows users to review clustered groups rather than individual results sequentially, maintaining completeness while reducing manual review time through structured presentation of results.
Solution Approach 2:
The system performs preliminary clustering and identification of dominant features before user review. By pre-organizing results into meaningful groups and highlighting key characteristics, the system prepares results in advance, reducing the time users need to spend on manual analysis while preserving all relevant information.
2Loss of information
If search engines return all ranked search results, then completeness of search results is improved, but user effort increases
Solution Approach 1:
Results are divided into clusters that group similar items together, reducing the cognitive load on users. Instead of evaluating each result individually, users can assess clustered groups based on dominant features, significantly reducing user effort while maintaining access to complete result sets.
Solution Approach 2:
The clustering system acts as an intermediary between the search engine and user, automatically analyzing and organizing results before presentation. This intermediary layer processes the complexity of result evaluation, presenting simplified cluster representations that reduce user effort while preserving information completeness.
3Measurement precision
If search results are ranked by confidence level, then accuracy of matching is improved, but duplication of results increases
Solution Approach 1:
The patent segments results into clusters that group duplicate or highly similar results together. By organizing results based on similarity rather than just confidence ranking, the system maintains accurate matching while visually presenting duplicates as grouped entities, helping users quickly identify and skip redundant results.
Solution Approach 2:
Duplicate or highly similar results are merged into single clusters representing groups of equivalent results. This merging reduces the apparent quantity of duplicate results while maintaining the accuracy of matching, as users can assess one cluster representative rather than reviewing multiple identical results separately.
Data Source
AI summary
Techniques for summarization of search results are provided. A similarity search query comprising at least one search criteria is received. The similarity search query is executed on at least one data source containing a plurality of images associated with metadata responsive to the search criteria. A plurality of search results response to the similarity search query is received from the at least one data source. The plurality of search results is clustered based on the metadata associated with the plurality of search results excluding the similarity criteria. The plurality of search results is summarized based on the results of the clustering. The summarization is displayed in a display view. An interactive user interface is provided to refine the plurality of search results based on the summarization.