Intelligent learning application based on optical character recognition and personalized recommendation algorithms

Shengming Zhang; Zhihong Pan; Weinan Wang; Jinghao Zhou; Shenyin Wan; Kangdong Chen; Jinhong Chen; Donglin Wu

doi:10.1117/12.3004198

11 October 2023 Intelligent learning application based on optical character recognition and personalized recommendation algorithms

Shengming Zhang, Zhihong Pan, Weinan Wang, Jinghao Zhou, Shenyin Wan, Kangdong Chen, Jinhong Chen, Donglin Wu

Author Affiliations +

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128003K (2023) https://doi.org/10.1117/12.3004198
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

This paper proposes an intelligent learning application based on OCR (Optical Character Recognition) text recognition and a personalized recommendation algorithm, which can help students to record their mistakes and recommend similar questions according to the type of mistakes so that students can further consolidate their mistakes and improve their correctness rate in their daily work. This paper is based on the JAVA language for development and design. The user side is presented in the form of a WeChat applet, which reduces the use threshold and increases the user's dependability. The project combines the functional features of OCR algorithms for regular and irregular text recognition. It adds the ability to recognize distorted and blurred fonts to print fonts, scanned text, and other horizontally positioned text, making it more relevant to everyday use scenarios. The personalized recommendation algorithm of the project adopts various recommendation algorithms respectively, among which the collaborative recommendation algorithm is divided into user-based collaborative Filtering and item-based multi-criteria collaborative filtering, which perform relevant recommendations for user positive feedback exercises and the collaborative recommendation algorithm divided into user-based collaborative filtering and item-based multi-criteria collaborative filtering, which can predict users' preferences more accurately. The project also incorporates an exercise recommendation method that models the user's knowledge state, which models the user's personalized knowledge state based on their daily problem-solving habits, and makes exercise recommendations based on the model, which is a good predictor.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shengming Zhang, Zhihong Pan, Weinan Wang, Jinghao Zhou, Shenyin Wan, Kangdong Chen, Jinhong Chen, and Donglin Wu "Intelligent learning application based on optical character recognition and personalized recommendation algorithms", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128003K (11 October 2023); https://doi.org/10.1117/12.3004198

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KEYWORDS

Optical character recognition

Detection and tracking algorithms

Tunable filters

Education and training

Java

Data processing

Correlation coefficients

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