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Reseach Article

A Book Recommendation Algorithm Considering User Development

by Hu Daiping, Tang Ming
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 27
Year of Publication: 2019
Authors: Hu Daiping, Tang Ming
10.5120/ijca2019919731

Hu Daiping, Tang Ming . A Book Recommendation Algorithm Considering User Development. International Journal of Computer Applications. 177, 27 ( Dec 2019), 6-10. DOI=10.5120/ijca2019919731

@article{ 10.5120/ijca2019919731,
author = { Hu Daiping, Tang Ming },
title = { A Book Recommendation Algorithm Considering User Development },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2019 },
volume = { 177 },
number = { 27 },
month = { Dec },
year = { 2019 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number27/31067-2019919731/ },
doi = { 10.5120/ijca2019919731 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:47:03.014146+05:30
%A Hu Daiping
%A Tang Ming
%T A Book Recommendation Algorithm Considering User Development
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 27
%P 6-10
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There commonly exists the problem of unsatisfactory recommendations given by book recommendation systems. Aiming at the developing characteristic of library user group in university which reflects the consistency between the book borrowing sequence and the accumulation of knowledge, the paper introduces the book lists borrowed by similar users in user group with different development stage to the application of collaborative filtering algorithm in order to increase effective information contained by the whole recommendation process. Consequently, the consistency of the recommendation results and the actual needs of users is improved while the performance of recommendation system rises. The effectiveness of the introduction of user development stage is shown and proved by experiments.

References
  1. Li Min, Wang Yingchun and Liu Yanquan, Investigation on the Recommendation System of Collection Resources in University Library of "211 Project", Library and Information Service, 2016, (9): 55–60.
  2. Huang Yan, Research and Design of Bibliographic Recommendation System in the Library, Library Research, 2011, 41(2): 92–96
  3. Xie Linhui, Research on the Application of Recommendation System in University Digital Library, Modern Intelligence, 2006, 26(11): 72–74, 2006.
  4. Dong Kun, Research on Book Recommendation System of University Library based on Collaborative Fltering Algorithm, Modern Library and Information Technology, 2011, (11): 44–47.
  5. Yao Wang, Book Recommendation System of University Library for Students, Journal of West Anhui University, 2014, (4): 149–152.
  6. Liu Kai, Wang Weijun, Huang Yinghui and Fang Wei, “Theoretical Exploration of Personalized Recommendation System: From System to User-Centered Evolution”, Intelligence Theory and Practice, 2016, 39(3): 52–56.
  7. Xu Jiali and Chen Jia, A Fast Personalized Bibliographic Recommendation Method, Modern Library and Information Technology, 2010, 26(2): 79–84.
  8. Dou Lingyuan, Wang Xinhua, and Sun Ke, Collaborative Filtering Recommendation Algorithm Integarting Tag Feature and Time Context, Small Microchip Systems, 2016, 37(1): 48–52.
  9. Zhang Wenhua, Hu Chun, Hu Guanglin and Feng Kai, “Research on Clustering Analysis Based on Library Circulation Data”, Journal of Agricultural Library and Information Science, 2010, 22(1): 109–111.
  10. Li Shuqing, Xu Xia and Xu Minjia, The Measurement Method of Book Referral Quality and the Personalized Book Recommendation Service based on the Binary Network of Readers' Lending and Reading, Journal of Library Science of China, 2013, 39(3): 83–95.
  11. Li Weihua, Lu Yumin and Mei Hong, Discussion on Personalized Information Recommendation System of Digital Library, Science and Technology Plaza, 2007, (9): 109–110.
  12. Yang Xu, Research on Collaborative Filtering Algorithm based on User Context Information, Jilin University, 2014.
Index Terms

Computer Science
Information Sciences

Keywords

Book Recommendation Recommendation Algorithm User Development Academic Library