Implicit Metadata Extraction for Data Store Searchability

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Solution Overview

Problem

Existing data stores are not easily searchable by users unfamiliar with their schema, as they require specific queries to generate metadata, which may not include relevant keywords, limiting accessibility.

Innovation Solution

Implementing an implicit metadata system that monitors usage and communication to extract keywords and associate them with the data store metadata, allowing for semantic discovery without creator intervention, and making these keywords available for search queries.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If data store owners manually create queries to generate metadata, then the data store becomes searchable, but the process requires owner intervention and may not include relevant keywords that match searcher terms

Engineering Contradiction:

ImprovesearchabilityVSAvoidmetadata generation process

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system automatically generates metadata by monitoring usage and communication patterns without requiring owner intervention. The data store serves itself by extracting keywords from actual usage, eliminating the need for manual metadata creation while improving relevance to searcher needs

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses feedback from actual usage and communication patterns to continuously improve metadata quality. By monitoring how the data store is actually used and discussed, the system extracts keywords that reflect real-world relevance rather than relying on owner assumptions

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If the data store schema is complex or unfamiliar, then the data store can store sophisticated data, but users unfamiliar with the schema cannot effectively search or discover the data

Engineering Contradiction:

Improvedata storage capabilityVSAvoiddata discovery

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system introduces an intermediary layer of usage-based metadata that sits between the complex data store schema and user search queries. This intermediary metadata, derived from actual usage patterns, translates complex schema structures into accessible keywords that users can understand and search without knowing the underlying schema

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces the mechanical approach of manual schema-based searching with an automated system that extracts keywords from usage patterns. Instead of requiring users to navigate complex schema structures, the system substitutes automatic keyword extraction from communication and usage data

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If metadata is generated without owner intervention, then the process becomes automated and scalable, but there is a risk that extracted keywords may not accurately represent the data store content

Engineering Contradiction:

Improvemetadata generation efficiencyVSAvoidkeyword accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system uses feedback from actual usage and communication patterns to ensure keyword accuracy. By monitoring real-world interactions with the data store, the system extracts keywords that naturally reflect the data's purpose and content, providing automated generation with inherent accuracy validation

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system continuously monitors usage and communication patterns to continuously refine and update metadata. This ongoing process ensures that keywords remain accurate and relevant as the data store evolves, maintaining reliability through continuous validation against actual usage

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS11745093B2Developing implicit metadata for data stores

Publication Date: 2023.09.05 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

A system enables metadata to be gathered about a data store beginning from the creation and generation of the data store, through subsequent use of the data store. This metadata can include keywords related to the data store and data appearing within the data store. Thus, keywords and other metadata can be generated without owner/creator intervention, with enough semantic meaning to make a discovery process associated with the data store much easier and efficient. Usage of or communication regarding a data store are monitored and keywords are extracted from the usage or communication. The keywords are then written to otherwise associated with metadata of the data store. During searching, keywords in the metadata are made available to be used to attempt to match query terms entered by a searcher.