Query Federation via Popularity Analysis
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Solution Overview
Problem
Users face difficulties in selecting the appropriate search application that returns the best results, as existing methods require manual administration of query federations based on popularity, which is inefficient and not adaptive.
Innovation Solution
Implementing a system where query logs from additional result sources are analyzed to automatically determine query popularity, allowing queries to be federated and executed across multiple sources, with alterations made to improve relevance, and results are ranked and displayed accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual administration is used to maintain lists of queries to federate, then administrative control is maintained, but administrative burden increases and adaptability decreases
Solution Approach 1:
The system automatically monitors query popularity across result sources and performs federations without requiring manual administrative intervention. The federation process is self-managing, using automated logic to determine when and where to federate queries based on popularity metrics, thereby eliminating the administrative burden while maintaining adaptability.
Solution Approach 2:
The system pre-configures federation rules and popularity thresholds in advance, allowing it to automatically respond to query popularity changes without real-time administrative input. This preliminary setup enables the system to adapt dynamically while minimizing ongoing administrative complexity.
2Reliability
If queries are federated to multiple result sources, then result accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the federation process into distinct components: query popularity monitoring, federation decision-making, query execution across multiple sources, and result aggregation. Each component operates independently with well-defined interfaces, reducing overall system complexity while enabling federated searches across multiple result sources for improved accuracy.
Solution Approach 2:
The system introduces a federation management layer that acts as an intermediary between the user's query and multiple result sources. This intermediary handles the complexity of coordinating federated searches, managing query distribution, and aggregating results, thereby simplifying the overall system architecture while maintaining the ability to search multiple sources for improved result accuracy.
3Adaptability or versatility
If automatic determination of query popularity is implemented, then adaptability improves, but processing time increases
Solution Approach 1:
The system periodically updates query popularity metrics at scheduled intervals rather than continuously analyzing every query in real-time. This periodic approach allows the system to maintain accurate popularity data for automatic federation decisions while minimizing the processing time overhead, balancing adaptability with efficiency.
Solution Approach 2:
The system pre-computes and caches query popularity statistics in advance, allowing rapid automatic federation decisions without performing complex analysis at query time. This preliminary computation reduces processing time while maintaining the ability to adapt to popularity trends through pre-analyzed data.
Data Source
AI summary
A query received from a user is directed to a particular search application (e.g. an Enterprise search portal) that is associated with a result source from which to retrieve results. The received query may be federated to additional result sources when the received query is determined to be a popular query in a result source. Query logs associated with the additional result sources are analyzed to determine when a query is popular as compared to the original result source. The query may be altered before being executed that uses one or more of the additional result sources. When the query (altered/unaltered) is determined to be popular for any of the additional result sources as compared to the original result source, the query is executed using that additional result source.