AI Model Search Expansion for Data Completeness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search engines have limitations in indexing and retrieving specific types of data or data relationships, leading to difficulties in accessing relevant information, especially for novice users who must manually sift through complex search results or perform multiple searches to find desired information.
Innovation Solution
Implementing a novel search engine user interface that suggests and applies artificial intelligence (AI) models during a search session to expand search results by generating additional data that was not previously available, using augmentation AI models to refine and index this data for further searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search engines use standard indexing algorithms, then search results can be retrieved efficiently, but the search results are limited and do not include all relevant data relationships
Solution Approach 1:
The system pre-generates augmented data using AI models before the user performs searches. By anticipating potential search needs and pre-computing expanded data relationships, the system makes additional relevant data available without requiring complex real-time processing during the search operation itself.
Solution Approach 2:
AI models serve as intermediaries between the traditional search engine and the user. These models augment the original data with additional relationships and information, creating an expanded data set that the search engine can then query. The AI layer mediates between limited traditional search capabilities and the user's need for comprehensive results.
2Loss of information
If users perform multiple complex searches to find all relevant information, then more complete results can be obtained, but the operation becomes difficult especially for novice users
Solution Approach 1:
The system automatically performs data augmentation and result expansion without requiring user intervention. The AI models self-service by autonomously generating augmented data and the search engine automatically queries this expanded data, eliminating the need for users to manually perform multiple complex searches or understand sophisticated search syntax.
Solution Approach 2:
The system pre-computes augmented data and expands result sets before users need them. By anticipating that users want comprehensive information, the system proactively generates additional data relationships and makes them available in the search results, so users receive complete information in a single simple search operation.
3Loss of information
If users manually analyze search results to identify relationships, then relevant information can be found, but this requires sophisticated searchers and additional research
Solution Approach 1:
The system replaces manual user analysis with automated AI models. Instead of relying on users to manually examine results and identify relationships, AI algorithms automatically analyze the data, detect patterns, and generate augmented data that encodes relationships. This substitutes human cognitive effort with automated computational analysis.
Solution Approach 2:
AI models act as intermediaries that perform the analytical work between the raw data and the user. These models automatically identify relationships, generate insights, and expand the data with discovered connections, eliminating the need for users to directly perform sophisticated analysis themselves.
4Ease of operation
If search engines return a limited set of results, then the search operation remains simple, but users cannot access exhaustive search results without performing multiple complex searches
Solution Approach 1:
The system pre-generates expanded data sets and augments the original data with AI-generated content before searches are executed. By preparing comprehensive augmented data in advance, the system enables simple search operations to return exhaustive results, as the expanded data is already available for immediate retrieval.
Solution Approach 2:
AI models serve as intermediaries that expand the data set between the simple user query and the comprehensive results. The user submits a simple search, the AI models process this through augmented data sets, and return exhaustive results - maintaining interface simplicity while achieving result completeness through the AI mediation layer.
Data Source
AI summary
Expanding search engine functionality using AI models. A method includes, as part of a search session, receiving user input at a search engine. One or more searches on a set of data using the user input. Search results are provided from the one or more searches to a user. Based on a history of the search session, suggestions are provided in a user interface of AI models that could be applied to expand potential search results for the search session. User input is received at the user interface selecting one or more of the suggested AI model. The one or more selected AI models are applied to expand the set of data. Search results to the user based on searching the expanded set of data.