数字化促进阅读习惯的养成:改进后的混合图书推荐系统与流派导向型档案

IF 1.3 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Onur Dogan, Emre Yalcin, Ouranıa Areta Hiziroglu
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引用次数: 0

摘要

目的 阅读习惯对个人的个人成长和学业发展起着举足轻重的作用,因此必须鼓励校园用户养成阅读习惯。大学图书馆是促进阅读的重要平台,可提供各种书籍和资源。通过个性化系统推荐图书不仅能帮助校园用户发现新资料,还能提高他们对图书馆提供的服务的参与度和满意度,从而促进全面的学习体验。本研究提出了一种基于网络的解决方案--基于网络的混合智能图书推荐系统(W_HybridBook),该解决方案通过在生成图书推荐时考虑用户偏好和项目相似性,解决了冷启动问题和有限的可扩展性等难题。本文改进了传统的混合系统,在确定个体之间的相似性时,使用面向流派的配置文件(GOPs)代替用户的原始评分配置文件。基于消费的流派特征(W_HybridBook-CBP)是通过评估一个项目在数据集中是否获得过任何评分来创建的,而基于投票的流派特征(W_HybridBook-VBP)则是通过考虑基于用户评分大小的流派类别来生成的。比较结果表明,用户对 W\_HybridBook-VBP 特征生成的推荐相当满意,平均评分为 4.0633,精确度值为 0.7988。W\_HybridBook-VBP 在算法和推荐运行时间方面也是最快的。该系统主要通过整合著名的协同过滤策略和基于内容的过滤策略来提供基于排名的推荐。考虑到伊兹密尔巴基尔凯大学用户和学者的偏好,我们收集了一个数据集,该大学是学生人均图书数量最多的大学之一。更重要的是,该数据集已经发布并公开,供未来推荐系统领域的研究使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digitalization for enhancing reading habits: the improved hybrid book recommendation system with genre-oriented profiles

Purpose

Reading habit plays a pivotal role in individuals' personal and academic growth, making it essential to encourage among campus users. University libraries serve as valuable platforms to promote reading by providing access to a diverse range of books and resources. Recommending books through personalized systems not only helps campus users discover new materials but also enhances their engagement and satisfaction with the library’s offerings, contributing to a holistic learning experience.

Design/methodology/approach

This study presents a web-based solution, the Web-Based Hybrid Intelligent Book Recommender System (W_HybridBook), as a solution that addresses challenges like cold start issues and limited scalability by factoring in user preferences and item similarities in generating book recommendations. The paper improves the traditional hybrid system using Genre-Oriented Profiles (GOPs) instead of original rating profiles of users when determining similarities between individuals. Consumption-based genre profiles (W_HybridBook-CBP) are created by assessing whether an item has received any ratings in the dataset, and vote-based genre profiles (W_HybridBook-VBP) are generated by considering the genre categories based on the magnitude of the user’s rating.

Findings

The comparative results indicated that users are quite satisfied with the recommendations generated by W\_HybridBook-VBP profiling, with an average rating of 4.0633 and a precision value of 0.7988. W\_HybridBook-VBP is also the fastest way with respect to the algorithm and recommendation run time.

Originality/value

The proposed W\_HybridBook has been then enhanced by adopting two user profiling strategies to boost the similarity calculation process in the recommendation generation phase. This system provides ranking-based recommendations by mainly integrating well-known collaborative and content-based filtering strategies. A dataset has been collected by considering the preferences of both users and academics at Izmir Bakircay University, which is one of the universities with the highest number of books per student. More importantly, this dataset has been released and become publicly available for future research in the recommender system field.

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来源期刊
Library Management
Library Management INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
2.70
自引率
15.40%
发文量
30
期刊介绍: ■strategic management ■HRM/HRO ■cultural diversity ■information use ■managing change ■quality management ■leadership ■teamwork ■marketing ■outsourcing ■automation ■library finance ■charging ■performance measurement ■data protection and copyright As information services become more complex in nature and more technologically sophisticated, managers need to keep pace with innovations and thinking in the field to offer the most professional service with the resources they have.
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