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Ontology-based data storage for distributed knowledge bases

A knowledge base, distributed technology, applied in the field of knowledge base, can solve the problems of inefficient scalability, reduced efficiency, and inability to route queries effectively, and achieve the effect of reducing computing waste and improving efficiency

Pending Publication Date: 2022-06-03
IBM CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This is inefficient and does not scale well
Additionally, existing systems do not understand the underlying ontologies and capabilities of each data source, and thus cannot efficiently route queries
This reduces the efficiency of such systems, requiring significant computing resources to respond to typical queries

Method used

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  • Ontology-based data storage for distributed knowledge bases
  • Ontology-based data storage for distributed knowledge bases
  • Ontology-based data storage for distributed knowledge bases

Examples

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Embodiment Construction

[0031] Embodiments of the present disclosure provide an ontology-driven architecture that provides support for various query types using multiple data stores or nodes, each of which may have different capabilities. Advantageously, embodiments of the present disclosure enable efficient processing and routing of queries to diverse data stores based on existing ontologies, which improves system latency and reduces computational resources required to identify and return relevant data . In embodiments, the techniques described herein may be used to support various query applications, including natural language and conversational interfaces. The systems described herein can provide transparent access to underlying backend repositories via the Abstract Ontology Query Language (OQL), which allows users to express their information needs against a domain ontology.

[0032] In one embodiment, to provide improved performance for different query types, the system first optimizes the plac...

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Abstract

Techniques for distributed data placement are provided. Query workload information corresponding to a domain is determined by a data coordinator, and the query workload information is modeled as a hypergraph, where the hypergraph includes a set of vertices and a set of hyperedges, where each vertex in the set of vertices corresponds to a concept in an ontology associated with the domain. A mapping between the concept and the plurality of data nodes is generated based on the hypergraph and further based on the predefined capabilities of each of the plurality of data nodes. A distributed knowledge base is established based on the generated mapping.

Description

technical field [0001] The present disclosure relates to knowledge bases and, more particularly, to efficient data placement in distributed knowledge bases using ontologies. Background technique [0002] More and more businesses are leveraging knowledge bases (KBs) to enhance their analytics and improve the decision making, efficiency and effectiveness of their systems. Typically, within an enterprise's domain, a KB is relatively private. For example, financial institutions rely on KBs with significant financial knowledge, such as data related to government regulations in financial markets. Conversely, a healthcare enterprise may maintain a KB with a considerable amount of data collected from the medical literature. There is a substantial need for deep domain specialization, efficient systems, and efficient techniques for managing these KBs. Existing systems that are unaware of domain ontologies that provide an entity-centric view of the domain schema cannot efficiently m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50
CPCG06N5/022G06F16/367G06F16/9024G06F9/3891G06F16/9038G06F16/9035G06F18/2323
Inventor A.夸尔马F.奥兹坎R.阿罗泰比雷川
Owner IBM CORP
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