Vector Space Embeddings for Dynamic User Data Record Relationship Mapping

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Solution Overview

Problem

Existing customer relationship management (CRM) systems rely on user-defined relationships between users and data records, which can be incomplete and inaccurate, and require significant metadata storage, leading to storage overhead and data privacy concerns.

Innovation Solution

A database system determines user and data record relationships based on vector space embeddings generated from user and data record sessions, using embedding operations to create vectors that reflect real-time relationships without the need for user-generated definitions or extensive metadata storage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If user-defined relationships are used to track teams and colleagues, then relationship information can be stored, but the relationships become incomplete and inaccurate due to different security levels and dynamic changes

Engineering Contradiction:

Improverelationship accuracyVSAvoiduser configuration complexity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system automatically determines user relationships by analyzing metadata and domain knowledge without requiring users to manually define teams or colleagues. The relationship determination is performed self-service through computational analysis of user interactions, document access patterns, and communication data, eliminating the need for user configuration while improving relationship accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of user-defined relationship tracking with an automated computational system that uses metadata analysis and domain knowledge processing. This substitution transforms the relationship determination from a user-operated process to an automated information processing task, improving both accuracy and reducing operational complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If metadata and domain knowledge are collected to determine relationships, then relationship information can be obtained, but significant storage overhead and data privacy concerns arise

Engineering Contradiction:

Improverelationship information completenessVSAvoidmetadata storage volume

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The system extracts only the essential relationship information from metadata and domain knowledge through automated processing, rather than storing all raw metadata. By extracting key relationship indicators from user interactions, document access patterns, and communication data, the system obtains complete relationship information while minimizing storage requirements for processed relationship data.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent transforms raw metadata into processed relationship information by changing the data parameters from detailed interaction logs to aggregated relationship metrics. This parameter transformation reduces storage requirements while preserving the essential relationship information needed for team and colleague identification.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If custom data objects are created to track teams, then relationship tracking is possible, but inconsistencies arise from different users implementing different security levels

Engineering Contradiction:

Improverelationship tracking flexibilityVSAvoidrelationship consistency

Core Design Contradiction:

Adaptability or versatilityVSStability of the object's composition

Solution Approach 1:

The system uses a universal metadata analysis framework that processes various types of user interactions, document access patterns, and communication data through a single relationship determination mechanism. This universal approach eliminates inconsistencies by applying the same analytical rules across all users and data types, while maintaining the flexibility to handle different security levels and dynamic team compositions.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11475018B2Determining user and data record relationships based on vector space embeddings

Publication Date: 2022.10.18 SALESFORCE INC

AI summary

Methods, systems, and devices supporting determining user and data record relationships based on vector space embeddings are described. Some database systems may receive data record access indications corresponding to data records accessed by users. A database system may generate, based on the data record access indications, user sessions for the users, data record sessions for the data records, or a combination for users and data records. For example, a user session may correspond to a respective user and include a record identifier associated with each data record accessed by the user. The system may generate, in a vector space, vectors from the sessions using an embedding operation, where each vector corresponds to a respective user or data record. The system may determine relationships between the users, data records, or both based on the vectors and may transmit an indication of at least one data record based on the relationships.