Group Search Filtering Using Unwanted Result Feedback
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Solution Overview
Problem
Existing search engines fail to efficiently remove unwanted search results, leading users to miss important information buried in large result sets and rely on outdated methods like positive feedback or manual term modification.
Innovation Solution
A search tool that allows users to actively or passively indicate unwanted results, using AI to infer and remove similar results, and optionally suggest new search terms for improved relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users rely on traditional search engines to return large result sets, then comprehensive coverage is achieved, but users cannot efficiently locate important information buried in the results
Solution Approach 1:
The system extracts and removes unwanted search results from the result set based on user feedback. When users indicate certain results are unwanted, the system identifies and removes those results along with similar results, thereby extracting the harmful elements from the search results while preserving the valuable information.
Solution Approach 2:
Instead of requiring users to actively search for and identify wanted information among many results, the system inverts the approach by having users indicate unwanted results, then automatically removing those and similar results. This inversion transforms the user task from finding needles in haystacks to eliminating the haystack, making information retrieval more efficient.
2Measurement precision
If users manually modify search terms to find relevant information, then some relevance can be achieved, but the process is outdated and inefficient
Solution Approach 1:
The system implements a feedback mechanism where users provide input about unwanted search results, and the system uses this feedback to automatically refine and improve subsequent search results. This closed-loop feedback system continuously learns from user interactions and adjusts the search output to better match user preferences, eliminating the need for manual term modification.
Solution Approach 2:
The system performs self-service by automatically analyzing user feedback and adjusting search results without requiring users to manually modify search terms. The system autonomously identifies patterns in unwanted results and applies learned preferences to future searches, saving users time and effort.
3Quantity of substance
If search engines return all possible results, then completeness is maintained, but users miss important information due to information overload
Solution Approach 1:
The system converts the harmful effect of information overload into a benefit by using user feedback about unwanted results to intelligently filter and refine the result set. The overwhelming quantity of results becomes manageable through automated removal of unwanted items, transforming the curse of big data into a curated, relevant subset that highlights important information.
4Ease of operation
If users indicate unwanted results, then control over search outcomes is improved, but the system must process and analyze user feedback to infer similar results
Solution Approach 1:
The system uses an intermediary AI/ML component that mediates between user feedback and search result generation. This intermediary layer processes user indications of unwanted results, infers similarities, and automatically removes relevant results without requiring complex user actions. The intermediary handles the computational complexity while presenting a simple interface to users.
Data Source
AI summary
In accordance with some embodiments, processes and interfaces provide for enhancing search results of a group research project. For example, members of a group may be provided with information regarding other group member's search activities and/or be restricted from viewing certain search results (e.g., search results that are most popular with the public for a given search term, that are most popular with the group for the given search term or for the project, and/or search results that are restricted by a group manager).