Rule-Matched Information Recommendation for Lower Processing Load

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Solution Overview

Problem

Existing information recommendation technologies consume many processing resources when recommending information to specific groups of people, as they often send recommendations to all users, leading to inefficiency.

Innovation Solution

An information recommendation method and apparatus that obtain text data from clients, determine if it matches predetermined rules, and only retrieve relevant information from a second server if a matching rule is found, allowing for selective and efficient recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If information is recommended to all users, then the coverage of information recommendation is improved, but the processing resource consumption increases

Engineering Contradiction:

Improvecoverage of information recommendationVSAvoidprocessing resource consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The user base is segmented into different groups based on text data characteristics and predetermined rules. Instead of treating all users uniformly, the system divides users into segments that match specific information recommendation rules, allowing targeted recommendations only to relevant segments rather than all users.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary actions by establishing predetermined information recommendation rules before the actual recommendation process. These rules are set in advance based on text data patterns, enabling the system to quickly determine user-group matching without complex real-time analysis, thus reducing processing resources during recommendation execution.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If information is recommended to all users, then the reach of information recommendation is improved, but the processing time increases

Engineering Contradiction:

Improvereach of information recommendationVSAvoidprocessing time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

Users are segmented into predefined groups based on text data characteristics. This segmentation allows the system to quickly identify which user group a user belongs to and apply corresponding recommendation rules, significantly reducing the time required compared to analyzing each user individually or broadcasting to all users.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Information recommendation rules are predetermined and prepared in advance for different user groups. When a user's text data matches a predetermined rule, the system can immediately retrieve and apply the corresponding recommendation without performing complex real-time analysis, thus reducing processing time while maintaining broad reach.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11113743B2Information recommendation based on rule matching

Publication Date: 2021.09.07 ADVANCED NEW TECHNOLOGIES CO LTD

AI summary

Text data transmitted by a user device to a first server is retrieved. The text data is processed to determine whether an information recommendation rule set includes an information recommendation rule matching the text data. The information recommendation rule is set based on a recommendation information. If the information recommendation rule set includes the information recommendation rule matching the text data, the recommendation information is retrieved from a second server. A recommendation based on the recommendation information is transmitted to the user device.