Federated Search System Query Classification and Result Ranking
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Solution Overview
Problem
Current search protocols often fail to provide accurate and customized search results due to their inability to effectively classify and prioritize search queries across multiple data sources, leading to suboptimal user experiences.
Innovation Solution
A federated search system that classifies search queries, identifies relevant data sources, extracts features from search results, generates clusters, and ranks them using optimization criteria to provide a unified and relevant search result interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data sources are searched simultaneously to provide comprehensive results, then the quantity and coverage of search results improve, but the complexity of managing and ranking results from multiple sources increases
Solution Approach 1:
The patent segments the search system into multiple independent search providers, each responsible for specific data sources. The federated search protocol divides the overall search task into sub-tasks distributed across different providers, allowing comprehensive coverage while managing complexity through modular architecture. Each provider handles its own data sources independently, and results are aggregated at the protocol level.
Solution Approach 2:
The federated search protocol acts as an intermediary layer between the user and multiple search providers. It manages the complexity of coordinating multiple data sources by providing a unified interface that handles query distribution, result aggregation, and ranking. This mediator approach allows the system to search multiple sources simultaneously without exposing the underlying complexity to users or individual providers.
2Measurement precision
If search queries are classified and routed to specific data sources to improve accuracy, then the precision of search results improves, but the time required for query analysis and source selection increases
Solution Approach 1:
The patent implements preliminary classification of search queries into different types (e.g., web search, image search, news search) and pre-establishes mappings between query types and appropriate search providers. This preliminary action allows the system to quickly route queries to relevant data sources without performing complex analysis at query time, thus maintaining high precision while minimizing processing time.
Solution Approach 2:
The system changes the parameter of query routing from complex multi-factor analysis to simpler classification-based routing. By transforming queries into classified categories with predefined routing rules, the system achieves accurate source selection without the time cost of complex real-time analysis. The classification parameters enable efficient decision-making about which data sources to query.
3Reliability
If search results are clustered and ranked using optimization criteria to enhance relevance, then the quality and relevance of results improve, but the computational resources and processing time increase
Solution Approach 1:
The patent applies partial action by ranking and clustering only the top-K results from each search provider rather than processing all results. This selective approach maintains high relevance for the most important results while significantly reducing computational resources required. The system performs intensive ranking operations on a limited subset of results rather than attempting to optimize the entire result set.
Solution Approach 2:
The system applies different ranking and clustering strategies locally to different result sets based on their characteristics. Instead of using a single uniform ranking approach for all results, the patent tailors ranking criteria to specific result types and sources, improving overall relevance while optimizing computational efficiency. Each local result set receives appropriate processing intensity based on its importance and characteristics.
Data Source
AI summary
Systems and methods herein describe a network system for federated searching. The systems and methods receive a search query, transmit the search query to search providers, receive search results corresponding to the search query, extract metadata from each search result, generate matched groupings comprising a first search results that have matching metadata, generate a ranked list of the matched groupings and a plurality of relevance scores, identify a second subset of search results based on the ranked list of matched groupings, and cause display of the second subset of search results on a graphical user interface of a computing device.