Text Classification for Book Recommendation Accuracy
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Solution Overview
Problem
Users face inefficiency in finding desired books when browsing book recommendation topics, as existing search solutions often retrieve irrelevant or omitted book recommendations, diminishing the reading experience.
Innovation Solution
A text classification method that acquires and processes topic texts and tag description information to determine tag correlations, allowing for accurate identification of matching topic tags, thereby improving the accuracy of book recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users browse through each individual book recommendation topic to find desired books, then they can access book recommendations, but the efficiency of locating desired books is reduced
Solution Approach 1:
The patent replaces the mechanical browsing process (manually going through each topic) with an automated search system that uses keyword matching and text classification algorithms to directly identify relevant book recommendations, eliminating the need for sequential topic browsing
Solution Approach 2:
The patent introduces a search intermediary layer that processes user queries through keyword extraction, text feature extraction, and correlation calculation to bridge the gap between search keywords and relevant book recommendations, enabling direct access without manual browsing
2Measurement precision
If existing search solutions retrieve book recommendation topics matching search keywords, then search functionality is provided, but the recommended books may be irrelevant or omitted
Solution Approach 1:
The patent applies local quality by extracting and analyzing specific text features from both the topic text and tag description information, then calculating correlations between these localized features to determine the most relevant tags, rather than using generic keyword matching
Solution Approach 2:
The patent changes the search parameters from simple keyword matching to a multi-parameter evaluation system that includes text feature extraction, tag description feature extraction, and correlation coefficient calculation, enabling more precise and reliable book recommendations
Data Source
AI summary
A text classification method and apparatus, a text processing method and apparatus, a computer device and a storage medium are provided. The text classification method which is applied to a server, includes: acquiring a topic text to be classified and tag description information of at least one topic tag to be predicted; extracting a target text feature of the topic text to be classified, and extracting a tag description feature of the tag description information of each topic tag to be predicted; determining a tag correlation between the target text feature and each tag description feature to obtain at least one tag correlation; and determining a target topic tag matching with the topic text to be classified from the at least one topic tag to be predicted based on the at least one tag correlation.