Situational Recommender System for Heterogeneous Environments
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Solution Overview
Problem
Business users in heterogeneous system environments face challenges with information overload and inconsistent data recommendations due to fragmented user profiles and diverse security controls across different applications, making it difficult to recommend relevant resources effectively.
Innovation Solution
A situational recommender system that utilizes a graph-based data model to represent heterogeneous resources and relations, dynamically adapting to user context by generating situation statements and applying operators to update situations based on user interactions, thereby providing personalized and timely recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional recommender systems are used in heterogeneous system environments, then information overload problem can be addressed, but inconsistent data recommendations occur due to fragmented user profiles and diverse security controls
Solution Approach 1:
The patent merges multiple user profiles from different applications into a unified user profile that consolidates user activities, preferences, and contextual information across heterogeneous systems. This unified profile enables consistent recommendation generation while respecting diverse security controls through a centralized authorization mechanism that translates application-specific security requirements into a common framework.
Solution Approach 2:
The patent introduces an intermediary recommendation engine that sits between diverse applications and users, translating heterogeneous data formats and security controls into a unified recommendation framework. This intermediary layer processes events from multiple applications, applies appropriate security policies, and generates consistent recommendations without requiring changes to the underlying heterogeneous systems.
2Adaptability or versatility
If multiple applications with different security controls are integrated, then resource accessibility is improved, but recommendation accuracy deteriorates due to fragmented user data
Solution Approach 1:
The patent combines fragmented user data from multiple applications with different security controls into a unified user profile structure. This merging process preserves the original security constraints while creating a comprehensive view of user behavior and preferences, enabling accurate recommendations across heterogeneous resources without sacrificing security or data completeness.
3Loss of time
If traditional recommender systems recommend items based on past preferences, then navigation efficiency is improved, but relevance to current context is reduced
Solution Approach 1:
The patent implements a dynamic recommendation approach that continuously updates user profiles and recommendation results based on real-time events and changing user context. Instead of relying solely on historical preferences, the system adapts recommendations to current situations by processing events from multiple applications and adjusting the unified user profile accordingly, ensuring both navigation efficiency and contextual relevance.
Data Source
AI summary
Situational recommendations in heterogeneous system environment are described herein. An event is received, where the event represents an interaction between an agent and a first resource from a number of resources available at the heterogeneous system environment. At least one impacted situation of a number of situations is determined based on the event. At least one operator from a number of operators is determined to apply on the at least one impacted situation. The at least one operator updates the at least one impacted situation. Recommendation of a second resource from the number of resources is generated based on the updated situation.