Context-Aware Semantic Search for Decentralized Social Machines
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Solution Overview
Problem
There is a need for an effective search service that enables searching and exploring content across decentralized networks of social machines, considering the context of entities within these networks.
Innovation Solution
A search service that receives a search query from a machine, determines its context using a semantic graph of the network, and identifies relevant services to provide answers based on the query type and context, utilizing a natural language understanding module and a semantic layer to build search contexts and retrieve relevant results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search methods are used in decentralized networks, then search coverage can be achieved, but search accuracy and context awareness deteriorate
Solution Approach 1:
The patent introduces a semantic layer as an intermediary between the search query and the decentralized network content. This semantic layer uses ontologies and knowledge graphs to mediate the search process, enabling context-aware querying while maintaining search accuracy across distributed sources without requiring centralized control
Solution Approach 2:
The patent adds a semantic dimension to traditional search by incorporating ontologies, knowledge graphs, and entity relationships. This transforms the search from simple keyword matching to multi-dimensional semantic querying, improving both accuracy and context awareness simultaneously
2Measurement precision
If context-aware searching is implemented using semantic graphs, then search accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the search system into distinct modular components: the semantic layer with ontologies, the knowledge graph engine, the query processing module, and the decentralized content sources. Each component has a specific function, reducing overall system complexity while maintaining high search accuracy through specialized processing at each stage
3Adaptability or versatility
If decentralized network searching is enabled, then search coverage and accessibility improve, but information retrieval efficiency deteriorates
Solution Approach 1:
The patent implements preliminary action through pre-built ontologies, knowledge graphs, and indexed semantic relationships in the semantic layer. These structures are constructed in advance to enable efficient querying of decentralized content, allowing the system to quickly retrieve relevant information without scanning entire networks during actual search operations
Data Source
AI summary
A method includes receiving, at a search toolbar, a search query from a machine in a network. The machine has an associated machine profile for participating in the network as an entity. The machine profile includes a machine identifier and machine metadata. A query type is determined from the search query. A search context for the machine is determined using a semantic graph of the network. From a set of services for the network, one or more relevant services to respond to the search query are identified based on the query type and the search context. The search query is applied to the one or more relevant services to obtain a set of responses. A set of relevant results for the search query is determined from the set of responses. The set of relevant results is transmitted to the machine.