Centralized Alert Distribution via Semantic Relevance Metrics
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Solution Overview
Problem
Providers of professional services face inefficiencies in processing and distributing large amounts of information to identify relevant news updates for their clients, as existing methods require computationally intensive processing across multiple network nodes, leading to increased costs and memory usage.
Innovation Solution
A centralized information provider processes anonymized client data and news events using semantic rules to generate relevance metrics, distributing electronic alerts efficiently to service providers, who can then deliver them to clients, thereby reducing processing load and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If information processing is distributed across multiple network nodes (service providers), then each provider can independently process and distribute alerts to their clients, but the overall system complexity and computational cost increase significantly
Solution Approach 1:
The patent introduces a centralized information provider as an intermediary that performs semantic rule processing and generates relevance metrics. This mediator handles the complex information processing tasks, while service providers receive pre-processed alert messages with distribution recommendations, thereby reducing their computational burden and simplifying the overall system architecture.
Solution Approach 2:
The patent consolidates multiple information processing functions (semantic rule application, relevance metric generation, client matching) into a single centralized information provider. This merging of functions at one node eliminates the need for each service provider to independently perform these complex operations, reducing system complexity while maintaining distribution capabilities.
2Measurement precision
If semantic rule processing is performed at multiple service provider nodes, then each provider can accurately match alerts to their clients, but the computational cost and memory usage increase significantly
Solution Approach 1:
The centralized information provider acts as an intermediary that performs the computationally intensive semantic rule processing and generates relevance metrics for all clients. Service providers receive these pre-computed metrics and use them to distribute alerts without performing their own semantic analysis, thereby maintaining matching accuracy while dramatically reducing computational cost at each node.
Solution Approach 2:
The system performs semantic rule processing and relevance metric generation in advance at the centralized information provider, before alerts need to be distributed. This preliminary action ensures that when service providers receive alerts, the matching work has already been completed, maintaining accuracy while eliminating redundant computational operations.
3Productivity
If a centralized information provider processes all information, then processing efficiency increases and service providers' systems are less burdened, but the centralized system requires robust semantic rule processing capabilities
Solution Approach 1:
The patent consolidates all semantic rule processing and relevance metric generation functions into the centralized information provider. This merging allows the system to leverage the full computational resources of one node for complex processing, improving overall productivity while concentrating the difficulty of semantic rule processing in a single location that can be optimized independently.
Data Source
AI summary
In response to receiving a text describing a news event, a centralized information provider applies semantic rules to the text to determine to which client attributes the text corresponds. The centralized information provider retrieves, from an electronic database, (i) identifiers for multiple clients, (ii) a set of client attributes for each of the clients, and (iii) for each of the clients, an identifier of a respective service provider. The centralized information provider then generates a metric of relevance of the news event for each of the clients, based on the client attributes of the client and the client attributes to which the text was determined to correspond. The centralized information provider transmits, to at least one service provider, an electronic alert message descriptive of the news event and an indication of a set of clients of the service provider for distribution to some or all of the set of clients.