AI Information Processing System for Targeted User Interest Acquisition
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Solution Overview
Problem
Existing AI technologies face challenges in accurately acquiring users' points of interest from vast network information, making targeted information push inefficient.
Innovation Solution
An AI-based method and apparatus that acquires a search record set, matches it with encyclopedia and microblog topic sets, selects points of interest based on matching results, and combines them to create a comprehensive set of points of interest, using feature vectors and pre-trained classification models to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional information push methods are used, then information can be delivered to users, but the accuracy of acquiring user points of interest is low
Solution Approach 1:
The patent segments the acquisition of user points of interest into multiple independent modules: search record analysis module, encyclopedia entry matching module, microblog topic matching module, and classification model module. Each module processes specific aspects of user interest extraction, allowing parallel processing and improving overall accuracy without requiring a complete system redesign.
Solution Approach 2:
The patent merges multiple data sources (search records, encyclopedia entries, microblog topics) and multiple processing methods (keyword matching, feature vector analysis, classification models) into a unified point of interest acquisition system. This combination leverages the strengths of each source to compensate for individual weaknesses, significantly improving the accuracy of user interest identification.
2Measurement precision
If multiple data sources are processed to improve accuracy, then user interest acquisition improves, but system complexity increases
Solution Approach 1:
The patent performs preliminary processing on data sources before main analysis: search records are pre-filtered and cleaned, encyclopedia entries are pre-tagged with categories, and microblog topics are pre-processed for feature extraction. This preliminary action reduces the complexity of subsequent matching and classification operations by preparing data in advance.
Solution Approach 2:
The patent introduces intermediary components to manage complexity: feature vector representations serve as intermediaries between raw text data and classification models, matching result aggregation modules act as intermediaries between multiple data sources and the final point of interest output, and standardized interfaces mediate between different processing modules.
3Measurement precision
If comprehensive matching is performed with encyclopedia and microblog data, then point of interest accuracy improves, but processing time increases
Solution Approach 1:
The patent implements partial matching strategies: instead of comparing all search records against all encyclopedia entries and microblog topics, it uses feature vectors and classification models to identify and process only the most relevant subsets of data. This selective processing maintains high accuracy while significantly reducing overall processing time.
Solution Approach 2:
The patent employs periodic updates and batch processing: classification models are trained and updated periodically rather than continuously, data matching is performed in batches rather than real-time for all data, and results are aggregated and refined in periodic cycles. This approach balances processing thoroughness with time efficiency.
Data Source
AI summary
An artificial intelligence based method and apparatus for processing information. A specific embodiment of the method includes: acquiring a search record set within a preset time period; matching the search record set with an encyclopedia entry set, and selecting a first set of points of interest from the encyclopedia entry set according to a match result; matching the search record set with a microblog topic set, and selecting a second set of points of interest from the microblog topic set according to a match result; and adding the first set of points of interest and the second set of points of interest to a set of points of interest. This embodiment achieves an accurate acquisition of the points of interest, thus facilitating the implementation of a targeted information push.