research-article

AMiner Citation-Data Preprocessing for Recommender Systems on Scientific Publications

Authors:

Vaios Stergiopoulos,

Thalia Tsianaka,

Eleni TousidouAuthors Info & Claims

PCI '21: Proceedings of the 25th Pan-Hellenic Conference on Informatics

Pages 23 - 27

https://doi.org/10.1145/3503823.3503828

Published: 22 February 2022 Publication History

Abstract

Recommender Systems (RS) are used to find user’s interested items among a huge amount of digital information, recently called Big Data, with the purpose of making valuable personalized recommendations. These systems use data from digital, online libraries to train, test and evaluate system’s efficiency. Along this line, data preprocessing is an essential and valuable step to achieve information-preserving data reduction and, in addition, to create input files with the appropriate format needed by a RS. This paper describes our approach for data preprocessing using a scientific publications’ dataset (Computer Science) found in AMiner (https://www.aminer.org/). The proposed approach consists of two phases: creation of a collection of articles based on user preferences and preprocessing this collection. The experimental results demonstrate the value of our approach with at least 79.8% information-preserving data reduction.

References

[1]

[1] Tang et al. 2008. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’2008). pp.990-998. URL: https://www.aminer.org/ [accessed 2021-09-05]

[2]

[2]Tang, Jie. 2016. AMiner: Toward Understanding Big Scholar Data. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, (WSDM ’16), pp. 467

[3]

[3]DBLP Computer Science Bibliography: Schloss Dagstuhl – Leibniz Center for Informatics. URL: https://dblp.org/ [accessed 2021-08-30]

[4]

[4]Pub Med Central: US National Library of Medicine and National Inst. of Health. URL: https://www.ncbi.nlm.nih.gov/pmc/ [accessed 2021-08-30]

[5]

[5]M. Alfarhood and J. Cheng. 2020. CATA++: A Collaborative Dual Attentive Autoencoder Method for Recommending Scientific Articles, DOI 10.1109/ACCESS.2020.3029722

[6]

[6]X. Li and J. She. 2017. Collaborative variational autoencoder for recommender systems, in Proc. 23rd ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, Aug. 2017, pp. 305–314

[7]

[7]C. Hsieh et al. 2017. Collaborative metric learning, in Proc. 26th Int. Conf. World Wide Web (WWW), 2017, pp. 193–201

Digital Library

[8]

[8]X. Li and J. She. 2017. Relational Variational Autoencoder for Link Prediction with Multimedia Data, Thematic Workshops ’17, Oct. 23–27, Mountain View, CA, USA.

Digital Library

[9]

[9]W. Zhang et al. 2011. A comparative study of TF*IDF, LSI and multi-words for text classification, Expert Systems with Applications, Volume 38, Issue 3, Pages 2758-2765, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2010.08.066

Digital Library

[10]

[10]D.M. Christopher and S. Hinrich. 2001. Foundations of statistical natural language processing, (pp. 529–574), MIT Press, Cambridge, Massachusetts

[11]

[11]M.F. Porter. 1980. An algorithm for suffix stripping, Program, Vol. 14 No. 3, pp. 130-7

[12]

[12]M.F. Porter. 2001. Snowball: a language for stemming algorithms, URL: www.snowball.tartarus.org/texts/introduction.html [accessed 2021-09-01]

[13]

[13]W. Peter. 2006. The Porter stemming algorithm: then and now, DOI 10.1108/00330330610681295

[14]

[14]A. G. Jivani et al. 2011. A Comparative Study of Stemming Algorithms, Int. J. Comp. Tech. Appl., Vol 2 (6), 1930-1938, ISSN:2229-6093

[15]

[15]M. Rezghi and M. Nasiri. 2013. New Algorithm for RS based on Singular Value Decomposition Method.

[16]

[16]N. F. Al-Bakri, S. H. Hashim. 2018. Reducing Data Sparsity in Recommender Systems, Journal of Al-Nahrain University, Vol.21 (2), June, 2018, pp.138-147.

[17]

[17]X. Feng et al. 2019. The Deep Learning–Based Recommender System “Pubmender” for Choosing a Biomedical Publication Venue: Development and Validation Study, J Med Internet Res 2019;21(5):e12957.

[18]

[18]S. Pandya et al. 2016. A Novel Hybrid based Recommendation System based on Clustering and Association Mining, 2016 10th International Conference on Sensing Technology (ICST).

[19]

[19]A. Duhamel. 2003. A preprocessing method for improving data mining techniques. Application to a large medical diabetes database, Studies in Health Technology and Informatics, 01 Jan 2003. 14663998

[20]

[20]F. Coaquira and E. Acuna. 2007. Applications of rough sets theory in data preprocessing for knowledge discovery, in Proceedings of the World Congress on Engineering and Computer Science WCECS 2007, San Francisco, USA

[21]

[21]L. Shuai-dong et al. 2004. Clustering of web learners based on rough set, Wuhan University Journal of Natural Sciences, vol. 9, pp.542–546

[22]

[22]F. Questier et al. 2002. Application of rough set theory to feature selection for unsupervised clustering, Chemometrics and Intelligent Laboratory Systems, vol. 63, no. 2, pp. 155 – 167

[23]

[23]G. Obadi et al. 2010. A Tolerance Rough Set Based Overlapping Clustering for the DBLP Data, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, DOI 10.1109/WI-IAT.2010.286

[24]

[24]M. Burch et al. 2020. eDBLP: Visualizing Scientific Publications, VINCI 2020, December 8–10, 2020, Eindhoven, The Netherlands, https://doi.org/10.1145/3430036.3430052

Digital Library

[25]

[25]Q. Kang et al. 2018. Edge-Attributed Community Search for Large Graphs, ICBDR 2018, October 27–29, 2018, Weihai, China.

Digital Library

[26]

[26]A. Idri et al. 2018. A systematic map of medical data preprocessing in knowledge discovery, https://doi.org/10.1016/j.cmpb.2018.05.007

[27]

[27]Z. Zhao et al. 2018. Identifying advisor-advisee relationships from co-author networks via a novel deep model, https://doi.org/10.1016/j.ins.2018.07.064

[28]

[28]M. Charnine et al. 2020. Impact Factor of a Term: a Tool for Assessing Article’s Future Citations and Author’s Influence Based on and DBLP Collections

[29]

[29]A. Sharma and S. Durga Bhavani. 2019. A Network Formation Model for Collaboration Networks, G. Fahrnberger et al. (Eds.): ICDCIT 2019, LNCS 11319, pp. 279–294, 2019, https://doi.org/10.1007/978-3-030-05366-6_24

Cited By

Stergiopoulos VVassilakopoulos MTousidou ECorral A(2024)An academic recommender system on large citation data based on clustering, graph modeling and deep learningKnowledge and Information Systems10.1007/s10115-024-02094-766:8(4463-4496)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10115-024-02094-7
Stergiopoulos VTousidou EVassilakopoulos MCorral A(2023)Academic Recommender Systems, Status, Challenges and Opportunities2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345971(1-8)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345971
Wang JLi YLiang MLi A(2022)Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)10.1109/CCIS57298.2022.10016355(516-520)Online publication date: 26-Nov-2022
https://doi.org/10.1109/CCIS57298.2022.10016355
Show More Cited By

Index Terms

AMiner Citation-Data Preprocessing for Recommender Systems on Scientific Publications
1. Applied computing
  1. Computers in other domains
    1. Digital libraries and archives
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction
  2. Information systems applications
    1. Data mining
    2. Digital libraries and archives

Index terms have been assigned to the content through auto-classification.

Recommendations

Publications by faculty members indexed in Science Citation Index and Scopus: an Iranian case study

PurposeThe paper aims to report an investigation that was conducted to identify the scholarly publications by faculty members of the Allameh Tabataba'i University that were indexed in two international databases, Science Citation Index SCI and Scopus, ...
Acknowledgments in scientific publications: Presence in Spanish science and text patterns across disciplines

The acknowledgments in scientific publications are an important feature in the scholarly communication process. This research analyzes funding acknowledgment presence in scientific publications and introduces a novel approach for discovering text ...
Nobel Citation Effects on Scientific Publications: A Case Study in Physics
Abstract
The Nobel Prize has been a prominent research topic in Scientometrics. This study aims to explore Nobel citation effects, which refer to changes in the cumulative citation counts of publications after authors have won the Nobel Prize. ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

PCI '21: Proceedings of the 25th Pan-Hellenic Conference on Informatics

November 2021

499 pages

ISBN:9781450395557

DOI:10.1145/3503823

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

PCI 2021

PCI 2021: 25th Pan-Hellenic Conference on Informatics

November 26 - 28, 2021

Volos, Greece

Acceptance Rates

Overall Acceptance Rate 190 of 390 submissions, 49%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
93
Total Downloads

Downloads (Last 12 months)27
Downloads (Last 6 weeks)4

Reflects downloads up to 14 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Stergiopoulos VVassilakopoulos MTousidou ECorral A(2024)An academic recommender system on large citation data based on clustering, graph modeling and deep learningKnowledge and Information Systems10.1007/s10115-024-02094-766:8(4463-4496)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10115-024-02094-7
Stergiopoulos VTousidou EVassilakopoulos MCorral A(2023)Academic Recommender Systems, Status, Challenges and Opportunities2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA59645.2023.10345971(1-8)Online publication date: 10-Jul-2023
https://doi.org/10.1109/IISA59645.2023.10345971
Wang JLi YLiang MLi A(2022)Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)10.1109/CCIS57298.2022.10016355(516-520)Online publication date: 26-Nov-2022
https://doi.org/10.1109/CCIS57298.2022.10016355
Stergiopoulos VVassilakopoulos MTousidou ECorral A(2022)Hyper-parameters Tuning of Artificial Neural Networks: An Application in the Field of Recommender SystemsNew Trends in Database and Information Systems10.1007/978-3-031-15743-1_25(266-276)Online publication date: 29-Aug-2022
https://doi.org/10.1007/978-3-031-15743-1_25

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents