Digitalization for enhancing reading habits: the improved hybrid book recommendation system with genre-oriented profiles
| Date | 05 August 2024 |
| Pages | 489-505 |
| DOI | https://doi.org/10.1108/LM-03-2024-0030 |
| Published date | 05 August 2024 |
| Author | Onur Dogan,Emre Yalcin,Ouranıa Areta Hiziroglu |
Digitalization for enhancing
reading habits: the improved
hybrid book recommendation
system with
genre-oriented profiles
Onur Dogan
Izmir Bakircay University, Izmir, Turkey
Emre Yalcin
Sivas Cumhuriyet Universitesi, Sivas, Turkey, and
Ouranıa Areta Hiziroglu
Izmir Bakircay University, Izmir, Turkey
Abstract
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 resu lts indicated that user s are quite satisfied w ith the recommendatio ns
generated by W\_HybridBook-VBP profiling, with an average rating of 4.0633 and a precision value of
0.7988. W\_HybridBo ok-VBP is also the fast est way with respect to t he algorithm and reco mmendation
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.
Keywords Recommendationsystems, Book recommender, Reading habits, Consumption-based genre profile,
Vote-based genre profile
Paper type Research paper
Library
Management
489
We extend our heartfelt appreciation to Izmir Bakircay University, Smart University and Digital
Transformation Coordinatorship (https://sudt.bakircay.edu.tr/) for their generous support, scholarly
guidance, and access to their extensive resources, which greatly contributed to the success of this
research.
Conflict of interest: The authors declare that they have no conflict of interest.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0143-5124.htm
Received 3 March 2024
Revised 8 June 2024
Accepted 27 June 2024
Library Management
Vol. 45 No. 8/9, 2024
pp. 489-505
© Emerald Publishing Limited
0143-5124
DOI 10.1108/LM-03-2024-0030
1. Introduction
Reading habits play a crucial role in individuals’intellectual and emotional growth, as well as
their academic success. The ability to read well allows individuals to expand their knowledge,
broaden their perspectives, and develop critical thinking skills (Basantes and Basantes, 2023).
According to surveys on European and worldwide levels, Europeans are the world’s biggest
bookworms and spend at least one hour each day reading. Finland, Poland, and Estonia
harbor the most significant number of Europe’s readers, with 16.8% of Finnish citizens
claiming reading to be their favorite pastime. France, Romania, Austria, and Belgium have
fewer bookworms compared with the rest of the EU (Eurostat, 2018).
Regarding Turkiye and according to the report of the Ministry of National Education on
Leisure Time and Reading Habits, Turkey ranks low compared to other countries in terms of
reading, with just above 10% of the Turkish population reading books (Eurostat, 2018), and
Turkish citizens struggle to develop regular reading habits (Sur and Ates
¸, 2022). The most
common reason for not reading books is lack of time, followed by lack of interest (Chu, 2003).
In particular to students’reading habits, university libraries play a crucial role in
promoting reading and supporting students’academic endeavors (Samsuddin and Aspura,
2021). They provide access to a wide range of academic resources, including books, journals,
and digital materials. Even with the plethora of the aforementioned resources, Tsuji (2020)
discusses the preference of university students for Wikipedia articles over books, even when
they are within a library. This finding supports the claim that students in universities may
not be utilizing the books available in libraries as much as they should and suggests that
there is a need to encourage students to read library books more actively. A lack of
engagement with library resources may result in the underutilization of resources and
possible squandering of books and money (Connaway et al., 2017;Jiao et al., 1996). It is
essential for libraries to actively promote their resources and services so that they are
effectively utilized, maximizing the benefits for students and minimizing waste. Therefore, it
is fundamental to comprehend the reading patterns of university students in order to develop
strategies that effectively promote reading and improve students’academic performance.
Recommendation systems are essential because they help users discover new books and
resources, increase their engagement and satisfaction, and ultimately enhance the learning
experience as a whole (Wu et al., 2022). Especially in the digital age, where the abundance of
books can result in information saturation and make it difficult for users to locate books that
match their preferences, book recommendation systems are crucial (Khademizadeh et al.,
2022). Recommendation syst ems can mitigate this issue by pr oviding personalized
recommendations based on the user’s past actions or the characteristics of the books.
Moreover, they can play a significant role in enhancing the overall learning experience by
providing personalized recommendations and boosting student engagement and satisfaction
(Ifada et al., 2019).
Recommending books has become an essential research topic in the fields of information
retrieval and machine learning, as it enables users to discover new books and resources they
might not have discovered otherwise. Predicting a user’s preferences for a set of items (in this
case, books) based on their past behavior (e.g. ratings, purchase history, reading history,
borrowing duration) or attributes of the items themselves is essentially the problem of book
recommendation. Several factors, including the high dimensionality of the item space, the
sparsity of user-item interactions, and the subjectivity of user preferences, make book
recommendation a difficult task (Iqbal et al., 2020). Additionally, the substantial amount of
books available and the fast-paced growth of the book market make it challenging to provide
accurate and pertinent recommendations (Anwar and Uma, 2022).
Book genres are significant for making personalized recommendations. Genres are
categories that sort books depending on their content, writing style, and the demographic
they are marketed to. Examples of common book genres include fiction, non-fiction, mystery,
LM
45,8/9
490
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