Contextual Virtual Workspace Semantic Annotation

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Solution Overview

Problem

Business users face challenges in accessing relevant data within a virtual workspace due to the lack of semantic knowledge, making it difficult to identify relationships between modules and find critical information, especially when dealing with complex data from various sources and formats.

Innovation Solution

A contextual virtual workspace is implemented, which aggregates semantically proximate data, identifies user annotations, and provides semantic context to enable smart services by combining known information and user interactions, suggesting relevant content based on user behavior and social connections, and dynamically updates data in real-time using an in-memory database.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If data is collected from various content providers, then the quantity of available information increases, but the complexity of managing and identifying relevant information increases

Engineering Contradiction:

Improvequantity of informationVSAvoidcomplexity of managing information

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent introduces a semantic context layer as an intermediary between raw data from multiple content providers and the user. This semantic context layer processes, contextualizes, and prioritizes information, making it manageable despite the quantity of data sources. The system acts as a mediator that transforms diverse data into structured, meaningful contexts.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system automatically generates and maintains semantic context without requiring manual intervention. It self-updates by monitoring user interactions and data changes, automatically prioritizing information based on user behavior patterns and contextual relevance, thereby managing information complexity autonomously.

Inventive Principle:

Principle #25Self-service

2Quantity of substance

If the workspace provides comprehensive data from multiple sources, then the user has access to more information, but the user cannot easily identify relationships between modules

Engineering Contradiction:

Improvedata availabilityVSAvoidease of identifying relationships

Core Design Contradiction:

Quantity of substanceVSEase of operation

Solution Approach 1:

The semantic context serves as an intermediary that connects disparate data modules. It establishes meaningful relationships between information from different sources by contextualizing it according to user roles, business processes, and data relationships, making the connections visible and understandable to users.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system continuously monitors user interactions with data modules and uses this feedback to dynamically adjust and refine semantic contexts. This feedback mechanism ensures that relationships between modules are highlighted based on actual user needs and patterns, making identification easier over time.

Inventive Principle:

Principle #23Feedback

3Device complexity

If the workspace lacks semantic knowledge, then the system remains simple, but it cannot provide services that rely on semantic context

Engineering Contradiction:

Improvesystem simplicityVSAvoidcapability to provide semantic services

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The patent segments the semantic context functionality into separate, manageable components. Instead of building a monolithic semantic understanding system, it divides the context generation, maintenance, and utilization into distinct modules that can be independently developed and scaled, maintaining overall system simplicity while enabling semantic services.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The semantic context system operates autonomously, self-updating and self-adjusting based on user interactions and data changes. This self-service capability allows the system to develop semantic understanding without complex centralized control, maintaining simplicity while achieving adaptability.

Inventive Principle:

Principle #25Self-service

4Measurement precision

If relevant content is suggested based on user behavior and social connections, then the relevance of suggested content improves, but the complexity of analyzing user behavior patterns increases

Engineering Contradiction:

Improverelevance of suggested contentVSAvoidcomplexity of behavior analysis

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system focuses on analyzing only the most relevant aspects of user behavior rather than attempting to process all possible interaction data. It selectively monitors and analyzes key patterns such as module access sequences, search queries, and collaboration networks, providing sufficient behavioral insights for accurate content suggestion without excessive analysis complexity.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS9164990B2Annotating contextual workspaces

Publication Date: 2015.10.20 SAP PORTALS ISRAEL

AI summary

In some implementations, a method for providing user-based context to a virtual workspace includes generating a first virtual workspace viewable by a user on a graphical user interface. The virtual workspace comprises a plurality of workspace modules comprising first data aggregated from one or more data objects. The aggregated data is determined to be semantically proximate aggregated data in a second virtual workspace. User annotations assigned to the semantically-proximate aggregated data are identified. The user annotations are presented in the first virtual workplace viewable by the user.