|
|
Recommending Scientific Literature Based on Author Preference and Heterogeneous Information Network |
Wang Qinjie,Qin Chunxiu(),Ma Xubu,Liu Huailiang,Xu Cunzhen |
School of Economics & Management, Xidian University, Xi'an 710126, China |
|
|
Abstract [Objective] This study uses heterogeneous information network and author preference to improve the performance of scientific literature recommendation. [Methods] We proposed a new method using various semantic information. Firstly, we weighted the meta path in the heterogeneous information network of the scientific literature with the help of the author preference. Secondly, we used the DPRel algorithm to calculate the correlation between the author and the literature. Finally, we constructed the weighted author-literature matrix, and retrieved the recommendation list based on the descending order of the correlation. [Results] We examined our model with data sets from the Web of Science. Compared with the methods of single meta path, the average successful recommendation rate of the new algorithm was 6%, 8% and 6% higher in three datasets. The improvement rate of successful recommendation was 14.8%, 27.6% and 13.0%, respectively. [Limitations] In data preprocessing stage, the keywords were unified manually, which is unrealistic for massive data sets. [Conclusions] The proposed method could effectively improve the quality of scientific literature recommendation.
|
Received: 01 February 2021
Published: 15 September 2021
|
|
Fund:National Natural Science Foundation of China(71573199) |
Corresponding Authors:
Qin Chunxiu ORCID:0000-0002-7809-4145
E-mail: cxqin@xidian.edu.cn
|
[1] |
李楚桐, 莫赞. 基于协同过滤算法的推荐系统研究[J]. 信息通信, 2018(2):38-39.
|
[1] |
( Li Chutong, Mo Zan. Research on Recommendation System Based on Collaborative Filtering Algorithm[J]. Information & Communications, 2018(2):38-39.)
|
[2] |
刘旭晖. 融合主题多样性与影响力的科技文献推荐算法研究[J]. 情报理论与实践, 2017, 40(12):134-138.
|
[2] |
( Liu Xuhui. Research on Scientific and Technical Literature Recommendation Algorithm Based on Topic Diversity and Influence[J]. Information Studies: Theory & Application, 2017, 40(12):134-138.)
|
[3] |
古迎志, 董诚, 裴兵兵, 等. 基于术语抽取与分级匹配的项目指南推荐方法[J]. 情报工程, 2018, 4(3):58-66.
|
[3] |
( Gu Yingzhi, Dong Cheng, Pei Bingbing, et al. The Recommendation Approach Based on Term Extraction and Graduation Matching[J]. Technology Intelligence Engineering, 2018, 4(3):58-66.)
|
[4] |
Christakopoulou E, Karypis G. Local Item-Item Models for Top-N Recommendation[C]// Proceedings of the 10th ACM Conference on Recommender Systems. 2016: 67-74.
|
[5] |
Wang Z Y, Liu Y, Yang J J, et al. A Personalization-Oriented Academic Literature Recommendation Method[J]. Data Science Journal, 2015, 14. DOI: 10.5334/dsj-2015-017.
doi: 10.5334/dsj-2015-017
|
[6] |
刘佳奇, 王全民. 基于改进的用户协同过滤算法的高校个性化图书推荐系统[J]. 计算机与数字工程, 2020, 48(10):2458-2461, 2479.
|
[6] |
( Liu Jiaqi, Wang Quanmin. College Personalized Book Recommendation System Based on Improved User Collaborative Filtering Algorithm[J]. Computer & Digital Engineering, 2020, 48(10):2458-2461, 2479.)
|
[7] |
Pan L L, Dai X Y, Huang S J, et al. Academic Paper Recommendation Based on Heterogeneous Graph[C]// Proceedings of the 14th China National Conference, CCL 2015 and 3rd International Symposium, NLP-NABD 2015. 2015:381-392.
|
[8] |
吴燎原, 蒋军, 王刚. 科研社交网络中基于联合概率矩阵分解的科技论文推荐方法研究[J]. 计算机科学, 2016, 43(9):213-217.
|
[8] |
( Wu Liaoyuan, Jiang Jun, Wang Gang. Study of Scientific Paper Recommendation Method Based on Unified Probabilistic Matrix Factorization in Scientific Social Networks[J]. Computer Science, 2016, 43(9):213-217.)
|
[9] |
张力. 科技论文推荐算法研究[D]. 北京: 北京邮电大学, 2017.
|
[9] |
( Zhang Li. Research on Recommendation Algorithm of Scientific Papers[D]. Beijing: Beijing University of Posts and Telecommunications, 2017.)
|
[10] |
张琪, 章颖华. 情境感知的科技文献协同推荐方法研究[J]. 现代图书情报技术, 2012(2):10-17.
|
[10] |
( Zhang Qi, Zhang Yinghua. Research on an Approach of Context Aware Collaborative Recommend for Scientific & Technical Literatures[J]. New Technology of Library and Information Service, 2012(2):10-17.)
|
[11] |
朱祥, 张云秋, 惠秋悦. 基于学科异构知识网络的学术文献推荐方法研究[J]. 图书馆杂志, 2020, 39(8):103-110.
|
[11] |
( Zhu Xiang, Zhang Yunqiu, Hui Qiuyue. An Academic Literature Recommendation Method Based on Disciplinary Heterogeneous Knowledge Network[J]. Library Journal, 2020, 39(8):103-110.)
|
[12] |
赵传, 张凯涵, 梁吉业. 非对称的异质信息网络推荐算法[J]. 计算机科学与探索, 2020, 14(6):939-946.
|
[12] |
( Zhao Chuan, Zhang Kaihan, Liang Jiye. Asymmetric Recommendation Algorithm in Heterogeneous Information Network[J]. Journal of Frontiers of Computer Science & Technology, 2020, 14(6):939-946.)
|
[13] |
刘云枫, 孙平, 葛志远. 异构信息网络推荐研究进展[J]. 情报科学, 2020, 38(6):151-157.
|
[13] |
( Liu Yunfeng, Sun Ping, Ge Zhiyuan. Literature Review of Heterogeneous Information Network Recommendation[J]. Information Science, 2020, 38(6):151-157.)
|
[14] |
孙艺洲, 韩家炜. 异构信息网络挖掘:原理和方法[M]. 段磊, 朱敏, 唐常杰, 译. 北京: 机械工业出版社, 2016.
|
[14] |
( Sun Yizhou, Han Jiawei. Mining Heterogeneous Information Networks: Principles and Methodologies[M]. Translated by Duan Lei, Zhu Min, Tang Changjie. Beijing, China Machine Press, 2016.)
|
[15] |
Suo X T, Wei F, Yu K. Entity Recommendation via Integrating Multiple Types of Implicit Feedback in Heterogeneous Information Network[C]// Proceedings of 2017 IEEE International Conference on Data Mining Workshops. 2017: 781-786.
|
[16] |
王永贵, 梅轩玮. 非对称异构信息网络的模糊推荐算法[J]. 计算机工程与应用, 2020, 56(23):74-79.
|
[16] |
( Wang Yonggui, Mei Xuanwei. Fuzzy Recommendation Algorithm for Asymmetric Heterogeneous Information Networks[J]. Computer Engineering and Applications, 2020, 56(23):74-79.)
|
[17] |
Vahedian F, Burke R, Mobasher B. Weighted Random Walks for Meta-Path Expansion in Heterogeneous Networks[C]// Proceedings of the 10th ACM Conference on Recommender Systems. 2016:15-19.
|
[18] |
Zhang M X, Wang J H, Wang W. HeteRank: A General Similarity Measure in Heterogeneous Information Networks by Integrating Multi-type Relationships[J]. Information Sciences, 2018, 453:389-407.
doi: 10.1016/j.ins.2018.04.022
|
[19] |
Gupta M, Kumar P. Recommendation Generation Using Personalized Weight of Meta-paths in Heterogeneous Information Networks[J]. European Journal of Operational Research, 2020, 284(2):660-674.
|
[20] |
王根生, 潘方正. 融合加权异构信息网络的矩阵分解推荐算法[J]. 数据分析与知识发现, 2020, 4(12):76-84.
|
[20] |
( Wang Gensheng, Pan Fangzheng. Matrix Factorization Algorithm for Weighted Heterogeneous Information Networks[J]. Data Analysis and Knowledge Discovery, 2020, 4(12):76-84)
|
[21] |
张海霞, 吕振, 张传亭, 等. 一种引入加权异构信息的改进协同过滤推荐算法[J]. 电子科技大学学报, 2018, 47(1):112-116, 152.
|
[21] |
( Zhang Haixia, Lv Zhen, Zhang Chuanting, et al. An Improved Collaborative Filtering Recommendation Algorithm with Weighted Heterogeneous Information[J]. Journal of University of Electronic Science and Technology of China, 2018, 47(1):112-116, 152.)
|
[22] |
Shi C, Li Y T, Zhang J W, et al. A Survey of Heterogeneous Information Network Analysis[J]. IEEE Transactions on Knowledge & Data Engineering, 2017, 29(1):17-37.
|
[23] |
Sun Y Z, Han J W. Meta-Path-Based Search and Mining in Heterogeneous Information Networks[J]. Tsinghua Science and Technology, 2013, 18(4):329-338.
doi: 10.1109/TST.2013.6574671
|
[24] |
Gupta M, Kumar P, Bhasker B. HeteClass: A Meta-path Based Framework for Transductive Classification of Objects in Heterogeneous Information Networks[J]. Expert Systems with Applications, 2017, 68:106-122.
doi: 10.1016/j.eswa.2016.10.013
|
[25] |
Sun Y Z, Han J W, Yan X F, et al. PathSim: Meta Path-based Top-K Similarity Search in Heterogeneous Information Networks[J]. Proceedings of the VLDB Endowment, 2011, 4(11):992-1003.
doi: 10.14778/3402707.3402736
|
[26] |
Christakis N A, Fowler J H. Social Contagion Theory:Examining Dynamic Social Networks and Human Behavior[J]. Statistics in Medicine, 2013, 32(4):556-577.
doi: 10.1002/sim.5408
pmid: 22711416
|
[27] |
徐红艳, 王丹, 王富海, 等. 融合潜在狄利克雷分布与元路径分析的用户相关性度量方法[J]. 计算机应用, 2019, 39(11):3288-3292.
|
[27] |
( Xu Hongyan, Wang Dan, Wang Fuhai, et al. User Relevance Measure Method Combining Latent Dirichlet Allocation and Meta-Path Analysis[J]. Journal of Computer Applications, 2019, 39(11):3288-3292.)
|
[28] |
Gupta M, Kumar P, Bhasker B. DPRel: A Meta-Path Based Relevance Measure for Mining Heterogeneous Networks[J]. Information Systems Frontiers, 2019, 21(5):979-995.
doi: 10.1007/s10796-017-9811-x
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|