Recipient-Specific Content Fragment Learning for Mobile Input
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Solution Overview
Problem
Existing input methods for mobile terminals do not leverage recipient-specific intelligence for editing short messages or emails, leading to inefficiencies when frequently contacting recipients.
Innovation Solution
A method and device that learn and store content segments and word frequency statistics related to recipients, prompting frequently used words for rapid editing by generating mapping lists and using a sent-content editing module, learning module, editing-control module, storage module, and information-sending module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an existing input method with intelligent learning function is used, then the input method can learn the user's input habit and frequently-used words, but the input method cannot carry out intelligent learning on the basis of the recipient when the user edits the content of a short message or email
Solution Approach 1:
The patent segments the content into content segments based on recipient relationships and communication scenarios. The system divides the learning process into two parts: learning user input habits (existing function) and learning recipient-specific patterns (new function). This segmentation allows the system to handle different learning objectives separately while integrating them for comprehensive content generation.
Solution Approach 2:
The patent introduces a content generation module as an intermediary between the input method and the final content output. This intermediary component specifically processes recipient information and generates appropriate content segments, acting as a bridge that connects recipient data with the input method's existing intelligent learning capabilities.
2Productivity
If the user manually inputs content using an existing input method, then the input method can learn user habits, but the user cannot rapidly send messages to frequently contacted recipients
Solution Approach 1:
The system performs preliminary learning of recipient-specific content patterns during the user's normal communication history. Before the user needs to send a message, the system has already analyzed past communications and generated content segments tailored to each recipient. This preliminary action eliminates the need for the user to manually type content for frequent recipients.
Solution Approach 2:
The patent enables the input method to serve itself by automatically generating content based on learned recipient patterns. The system no longer requires the user to manually input content for frequent recipients; instead, the system self-generates appropriate content segments and presents them for selection, significantly reducing the user's input time.
3Adaptability or versatility
If the input method learns only user input habits, then the learning function is simple and focused, but the system cannot provide recipient-specific content suggestions
Solution Approach 1:
The patent segments the learning system into distinct functional modules: a learning module that processes communication history, a content generation module that creates recipient-specific content segments, and a presentation module that displays suggestions. This segmentation makes the complex system more manageable and maintainable while enabling recipient-specific adaptation.
Solution Approach 2:
The patent designs the content generation module to handle multiple functions: analyzing recipient relationships, generating content segments, and presenting suggestions. This multi-functional design reduces the need for separate components for each function, thereby managing complexity while achieving comprehensive recipient-specific adaptation.
Data Source
AI summary
A method and a device for rapidly editing sending content based on a receiver. A sending-content-learning module is used to learn sending content to generate a content fragment for a receiver, and perform word frequency statistics on the content fragment; a corresponding list is generated from receiver information, the content fragment, and the word frequency statistics, and is stored; for the receiver and the word frequency statistics, the content fragment is displayed for a sender to edit the sending content, so as to send the sending content to a corresponding receiver. When a user edits a short message or an email, a content fragment commonly used for a corresponding receiver is displayed in a display box, and a sender can rapidly complete editing by selecting a required content fragment, thereby facilitating fast and convenient input and improving the user experience.