Virtual Item Packet Matching Using AI Topic Analysis
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Solution Overview
Problem
Existing methods for determining the recipient of a virtual item packet in online games and social networking software lack consistency and accuracy due to subjective sender decisions and simple keyword recognition, leading to inaccurate matching outcomes.
Innovation Solution
Implement a method using natural language processing to analyze message content and determine matching degrees, allowing users to receive virtual items based on interaction messages that align with predefined topic information, enhancing the recognition process through trained AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword recognition method is used to determine message matching, then the determination process is simple and fast, but the matching accuracy is low and lacks flexibility
Solution Approach 1:
The patent replaces simple keyword recognition (mechanical matching) with natural language processing technology that uses trained models to understand and analyze message semantics. This substitution enables the system to accurately determine matching degrees between messages and topics while maintaining processing efficiency through automated AI-based analysis.
2Adaptability or versatility
If subjective determination by sender is used, then the process is flexible and adaptive, but the determination results are inconsistent and biased
Solution Approach 1:
The patent implements automated determination where the system independently analyzes message content against predefined topics using NLP technology. This self-service approach eliminates subjective bias from senders while maintaining flexibility through configurable topic definitions and weightings, ensuring consistent and reliable matching results.
Solution Approach 2:
The system provides feedback by calculating and returning matching degrees for messages against topics. This feedback mechanism enables objective evaluation of message relevance, ensuring consistent determination results while allowing flexible adjustment of topic definitions and matching criteria.
3Device complexity
If simple keyword matching is used, then the system complexity is low, but the ability to handle nuanced language is insufficient
Solution Approach 1:
The patent changes the parameters of message analysis from simple keyword matching to comprehensive NLP processing that includes semantic analysis, context understanding, and sentiment detection. This parameter transformation enables the system to handle nuanced language while maintaining manageable complexity through modular architecture and configurable analysis depth.
Data Source
AI summary
This application discloses an information processing method, apparatus, and device, and relates to the field of artificial intelligence (AI). The method includes displaying a user interface, the user interface comprising a received virtual item packet, and the virtual item packet comprising topic information; displaying the topic information of the virtual item packet; receiving an interaction message corresponding to a second user account, the interaction message being matched with target information to request to receive a virtual item in the virtual item packet, and the target information being the topic information or information associated with the topic information; and receiving the virtual item in the virtual item packet in response to matching the interaction message and the target information.