Paper Recommendation Based on Author-paper Interest and Graph Structure

The recommendation system can recommend information to users efficaciously, which helps many users to obtain information in different fields. The paper recommendation is a research topic to provide authors with personalized papers of interest. However, most existing approaches equally treat title and abstract as the input to learn the representation of a paper, ignoring the author's interest and structure information of the academic network. In the paper recommendation system, authors and papers and the interaction of their information have a crucial impact on the efficiency and accuracy of the recommendations. However, most recommendation systems are usually designed based only on users. Therefore, we propose a method based on the author's periodic interest and academic graph network structure to obtain as much effective information as possible to recommend papers. Extensive offline experiments on large-scale real data show that our method outperforms the representative baselines.

[1]  Giorgios Kollias,et al.  Context-Specific Recommendation System for Predicting Similar PubMed Articles , 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

[2]  Pietro Liò,et al.  Graph Attention Networks , 2017, ICLR.

[3]  Marcos André Gonçalves,et al.  A source independent framework for research paper recommendation , 2011, JCDL '11.

[4]  Fabio Stella,et al.  An LDA-Based Approach to Scientific Paper Recommendation , 2016, NLDB.

[5]  Dit-Yan Yeung,et al.  Collaborative Deep Learning for Recommender Systems , 2014, KDD.

[6]  Andrew McCallum,et al.  Ask the GRU: Multi-task Learning for Deep Text Recommendations , 2016, RecSys.

[7]  Edward Y. Chang,et al.  Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks , 2018, SIGIR.

[8]  Min-Yen Kan,et al.  Exploiting potential citation papers in scholarly paper recommendation , 2013, JCDL '13.

[9]  Chong Wang,et al.  Collaborative topic modeling for recommending scientific articles , 2011, KDD.

[10]  Chandra Bhagavatula,et al.  Content-Based Citation Recommendation , 2018, NAACL.

[11]  Achraf Gazdar,et al.  A new similarity measure for collaborative filtering based recommender systems , 2020, Knowl. Based Syst..

[12]  Ting Liu,et al.  Constructing Narrative Event Evolutionary Graph for Script Event Prediction , 2018, IJCAI.

[13]  Sean M. McNee,et al.  Enhancing digital libraries with TechLens+ , 2004, JCDL.

[14]  Yongfeng Zhang,et al.  Sequential Recommendation with User Memory Networks , 2018, WSDM.

[15]  Ah Chung Tsoi,et al.  The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.

[16]  Haitao Liu,et al.  Paper recommendation based on the knowledge gap between a researcher's background knowledge and research target , 2016, Inf. Process. Manag..

[17]  Xiaoyan Zhang,et al.  Leveraging Title-Abstract Attentive Semantics for Paper Recommendation , 2020, AAAI.

[18]  Hebatallah A. Mohamed Hassan.  Personalized Research Paper Recommendation using Deep Learning , 2017, UMAP.

[19]  C. Lee Giles,et al.  A system for automatic personalized tracking of scientific literature on the Web , 1999, DL '99.

[20]  Yuxiao Dong,et al.  A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations , 2017, KDD.

[21]  Min-Yen Kan,et al.  Scholarly paper recommendation via user's recent research interests , 2010, JCDL '10.

[22]  Jason Weston,et al.  Memory Networks , 2014, ICLR.

[23]  Yongliang Li,et al.  Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation , 2019, KDD.

[24]  P. B. Shola,et al.  Application of Content-Based Approach in Research Paper Recommendation System for a Digital Library , 2014 .

[25]  Xavier Bresson,et al.  Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.

[26]  Andrew McCallum,et al.  Automating the Construction of Internet Portals with Machine Learning , 2000, Information Retrieval.

[27]  Hebatallah A. Mohamed Hassan,et al.  BERT, ELMo, USE and InferSent Sentence Encoders: The Panacea for Research-Paper Recommendation? , 2019, RecSys.

[28]  Sophie Siebert,et al.  Extending a Research-Paper Recommendation System with Scientometric Measures , 2017 .

[29]  Maria R. Lee,et al.  Research Paper Recommender Systems on Big Scholarly Data , 2018, PKAW.

[30]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[31]  Konrad P. Körding,et al.  Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications , 2016, PloS one.

[32]  Donghyun Kim,et al.  Convolutional Matrix Factorization for Document Context-Aware Recommendation , 2016, RecSys.

[33]  Atsuhiro Takasu,et al.  Related paper recommendation to support online-browsing of research papers , 2011, Fourth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2011).

[34]  Jöran Beel,et al.  Mr. DLib: Recommendations-as-a-Service (RaaS) for Academia , 2017, 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL).