Entity-Linked App Suggestions for Incomplete Queries

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Users face challenges in accessing desired entities on client devices due to the need to accurately identify and launch applications, leading to repeated queries and resource consumption when queries are incomplete or inadequate.

Innovation Solution

An on-device system identifies associations between entities and applications based on historical queries, generating suggestions to automatically launch the appropriate application for the entity, reducing the need for multiple inputs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If users provide incomplete or inadequate queries to access entities, then the automated assistant cannot be responsive and no application is triggered, but this results in repeated attempts by the user leading to extensive consumption of computing and battery resources

Engineering Contradiction:

ImproveQuery input simplicityVSAvoidComputing and battery resource consumption

Core Design Contradiction:

Ease of operationVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary action by analyzing historical queries to pre-establish associations between entities and applications before the user makes their query. When a user provides an incomplete query, the system uses these pre-computed associations to automatically determine the intended application, eliminating the need for repeated user attempts and reducing computing resource consumption.

Inventive Principle:

Principle #10Preliminary action

2Ease of operation

If users provide incomplete or inadequate queries, then the automated assistant may not be responsive, but this leads to repeated attempts by the user to provide appropriate queries

Engineering Contradiction:

ImproveQuery input simplicityVSAvoidTime for repeated query attempts

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

3Reliability

If the system requires accurate identification of applications by users, then applications can be precisely triggered, but this increases the complexity of user interaction and may lead to errors

Engineering Contradiction:

ImproveApplication triggering accuracyVSAvoidUser interaction complexity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system performs self-service by automatically determining the intended application based on historical query patterns and entity associations, without requiring the user to manually specify the application. The system analyzes the entity mentioned in the query and autonomously selects the appropriate application, maintaining high triggering accuracy while significantly reducing user interaction complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses feedback from historical queries to improve its automatic application selection. By continuously learning from past user behavior patterns, the system refines its associations between entities and applications, enabling more accurate automatic triggering while keeping the user interface simple.

Inventive Principle:

Principle #23Feedback

4Extent of automation

If the system processes historical queries to determine entity-application associations, then automated suggestions can be generated, but this requires processing and storage of query data

Engineering Contradiction:

ImproveAutomatic application suggestionVSAvoidQuery processing and storage system

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The system extracts only the essential information needed for automation - the associations between entities and applications derived from historical queries. Rather than storing and processing all query data, the system extracts and stores only the relevant entity-application mapping information, reducing the complexity of the processing and storage requirements while maintaining automation capability.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS12353427B2Rendering suggestion for searching entity within application in response to determining the entity is associated with the application

Publication Date: 2025.07.08 GOOGLE LLC

AI summary

Implementations include recognizing entities in a user query received from a client device and determining whether any of the recognized entities is a personal entity using an entity database storing personal entities donated by applications installed at the client device. Application(s) or application action(s) can be determined based on entity information of the recognized entities, and suggestions can be generated to suggest the determined application(s) (or the determined application action(s)). For an application (or application action) determined based on a recognized entity that is determined as a personal entity, a suggestion for the application (or application action) can be boosted for display to a user of the client device.