Semantic Model Context Delta Recommender
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Solution Overview
Problem
Complex computer programs often require extensive information to be provided to users in complex contexts, making it difficult for users to determine the necessary input, and existing systems lack flexibility and maintainability in managing this information across different contexts and knowledge sources.
Innovation Solution
A system utilizing a semantic model that decouples information from context, allowing it to be identified and reused across different contexts through a recommender service, enabling efficient storage and flexible management of information, and allowing changes to knowledge sources and programs without affecting the context, with a context delta mechanism to update context states and map them to relevant information sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If information is directly assigned to each context in complex programs, then the information can be easily accessed for that specific context, but the storage efficiency decreases and the system becomes less flexible when changes are needed
Solution Approach 1:
The patent extracts information from its direct association with specific contexts and places it into a separate, centralized knowledge source. This allows information to be stored once and reused across multiple contexts through the semantic model and recommender service, reducing storage redundancy while maintaining easy access through context-gathering mechanisms that retrieve relevant information based on current context state.
Solution Approach 2:
The patent creates a universal information structure where a single knowledge source serves multiple contexts. The semantic model with its elements, attributes, and recommender services provides a multi-functional framework that can identify and retrieve appropriate information for any given context without requiring separate information storage for each context, thus improving both storage efficiency and flexibility.
2Loss of information
If extensive information is provided to users in complex contexts, then users receive comprehensive help, but the system becomes less maintainable and more difficult to update
Solution Approach 1:
The patent separates information management from program logic by extracting information into external knowledge sources. This allows specialized personnel to update information in the knowledge source without modifying the complex program itself, improving maintainability while ensuring users continue to receive comprehensive information through the context-gathering service that retrieves all relevant information based on the current context.
Solution Approach 2:
The patent introduces a semantic model and recommender service as intermediaries between the knowledge source and the user interface. These intermediaries manage the complexity of information retrieval, automatically gathering relevant information from the knowledge source based on context state and presenting it to users, thus maintaining information completeness while simplifying the update process through centralized knowledge source management.
3Stability of the object's composition
If information is tightly coupled with the complex program, then changes in the program automatically reflect in the information, but the system loses flexibility when knowledge sources need to be updated independently
Solution Approach 1:
The patent extracts information from tight coupling with the program by placing it in external knowledge sources accessible through the semantic model. This decoupling allows independent updates of knowledge sources without program modification, while the context-gathering service maintains stable integration by automatically retrieving updated information based on context state, thus achieving both flexibility and stability.
Solution Approach 2:
The patent implements a dynamic information retrieval system where the semantic model and recommender service adapt to changing context states. The system dynamically determines which information to retrieve from the knowledge source based on the current context, allowing flexible updates to knowledge sources while maintaining stable program-information integration through the dynamic context-gathering mechanism that automatically reflects changes.
Data Source
AI summary
A computer system for identifying information related to a context includes a context gathering service configured to receive context deltas from a runtime and to identify a current context state. A context delta describes a change from a previous context state to the current context state. The computer system also includes a semantic model with elements and attributes, wherein an element represents one or more context states and an attribute is assigned to the element. The computer system further includes a rule interpreter configured to map the current context state to a current element and a recommender service configured to identify information related to the context in a knowledge source. The recommender service is identified by one or more attributes at least one of which is assigned to the current element.