{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T19:28:01Z","timestamp":1791487681192,"version":"4.3.4"},"reference-count":124,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Technische Hochschule K\u00f6ln"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Digit Libr"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Scientific writing builds upon already published papers. Manual identification of publications to read, cite or consider as related papers relies on a researcher\u2019s ability to identify fitting keywords or initial papers from which a literature search can be started. The rapidly increasing amount of papers has called for automatic measures to find the desired <jats:italic>relevant<\/jats:italic> publications, so-called paper recommendation systems. As the number of publications increases so does the amount of paper recommendation systems. Former literature reviews focused on discussing the general landscape of approaches throughout the years and highlight the main directions. We refrain from this perspective, instead we only consider a comparatively small time frame but analyse it fully. In this literature review we discuss used methods, datasets, evaluations and open challenges encountered in all works first released between January 2019 and October 2021. The goal of this survey is to provide a comprehensive and complete overview of current paper recommendation systems.\n<\/jats:p>","DOI":"10.1007\/s00799-022-00339-w","type":"journal-article","created":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T12:05:43Z","timestamp":1664971543000},"page":"335-369","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Scientific paper recommendation systems: a literature review of recent publications"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5075-7699","authenticated-orcid":false,"given":"Christin Katharina","family":"Kreutz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5379-5191","authenticated-orcid":false,"given":"Ralf","family":"Schenkel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,5]]},"reference":[{"key":"339_CR1","doi-asserted-by":"publisher","unstructured":"Afsar, M.M., Crump, T., Far, B.H.: An exploration on-demand article recommender system for cancer patients information provisioning. In: FLAIRS Conference\u201921 (2021). https:\/\/doi.org\/10.32473\/flairs.v34i1.128339","DOI":"10.32473\/flairs.v34i1.128339"},{"issue":"3","key":"339_CR2","doi-asserted-by":"publisher","first-page":"1519","DOI":"10.3906\/elk-1908-19","volume":"28","author":"S Ahmad","year":"2020","unstructured":"Ahmad, S., Afzal, M.T.: Combining metadata and co-citations for recommending related papers. Turkish J. Electr. Eng. Comput. Sci. 28(3), 1519\u20131534 (2020). https:\/\/doi.org\/10.3906\/elk-1908-19","journal-title":"Turkish J. Electr. Eng. Comput. Sci."},{"key":"339_CR3","doi-asserted-by":"publisher","DOI":"10.12785\/ijcds\/110192","author":"L Ahmedi","year":"2021","unstructured":"Ahmedi, L., Rexhepi, E., Byty\u00e7i, E.: Using association rule mining to enrich user profiles with research paper recommendation. Int. J. Comput. Dig Syst. (2021). https:\/\/doi.org\/10.12785\/ijcds\/110192","journal-title":"Int. J. Comput. Dig Syst."},{"key":"339_CR4","doi-asserted-by":"publisher","unstructured":"Alfarhood, M., Cheng, J.: Collaborative attentive autoencoder for scientific article recommendation. In: ICMLA\u201919, pp. 168\u2013174. IEEE (2019). https:\/\/doi.org\/10.1109\/ICMLA.2019.00034","DOI":"10.1109\/ICMLA.2019.00034"},{"key":"339_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106438","volume":"210","author":"Z Ali","year":"2020","unstructured":"Ali, Z., Qi, G., Muhammad, K., Ali, B., Abro, W.A.: Paper recommendation based on heterogeneous network embedding. Knowl. Based Syst. 210, 106438 (2020). https:\/\/doi.org\/10.1016\/j.knosys.2020.106438","journal-title":"Knowl. Based Syst."},{"key":"339_CR6","unstructured":"Alzoghbi, A., Ayala, V.A.A., Fischer, P.M., Lausen, G.: PubRec: Recommending Publications Based on Publicly Available Meta-Data. In: LWA\u201915, CEUR workshop proceedings. vol. 1458, pp. 11\u201318. CEUR-WS.org (2015). http:\/\/ceur-ws.org\/Vol-1458\/D01_CRC69_Alzoghbi.pdf"},{"key":"339_CR7","doi-asserted-by":"publisher","unstructured":"Amami, M., Faiz, R., Stella, F., Pasi, G.: A graph based approach to scientific paper recommendation. In: WI\u201917, pp. 777\u2013782. ACM (2017). https:\/\/doi.org\/10.1145\/3106426.3106479","DOI":"10.1145\/3106426.3106479"},{"key":"339_CR8","doi-asserted-by":"publisher","unstructured":"Anand, A., Chakraborty, T., Das, A.: FairScholar: balancing relevance and diversity for scientific paper recommendation. In: ECIR\u201917, LNCS. 10193, 753\u2013757 (2017). https:\/\/doi.org\/10.1007\/978-3-319-56608-5_76","DOI":"10.1007\/978-3-319-56608-5_76"},{"key":"339_CR9","doi-asserted-by":"publisher","first-page":"9324","DOI":"10.1109\/ACCESS.2018.2890388","volume":"7","author":"X Bai","year":"2019","unstructured":"Bai, X., Wang, M., Lee, I., Yang, Z., Kong, X., Xia, F.: Scientific paper recommendation: a survey. IEEE Access 7, 9324\u20139339 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2018.2890388","journal-title":"IEEE Access"},{"key":"339_CR10","doi-asserted-by":"publisher","unstructured":"Balog, K., Radlinski, F.: Measuring recommendation explanation quality: the conflicting goals of explanations. In: SIGIR\u201920, pp. 329\u2013338. ACM (2020). https:\/\/doi.org\/10.1145\/3397271.3401032","DOI":"10.1145\/3397271.3401032"},{"key":"339_CR11","doi-asserted-by":"publisher","unstructured":"Barolli, L., Di\u00a0Cicco, F., Fonisto, M.: An Investigation of Covid-19 Papers for a Content-Based Recommendation System. In: 3PGCIC\u201922, pp. 156\u2013164. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-030-89899-1_16","DOI":"10.1007\/978-3-030-89899-1_16"},{"key":"339_CR12","unstructured":"Basaldella, M., Nart, D.D., Tasso, C.: Introducing distiller: a unifying framework for knowledge extraction. In: IT@LIA@AI*IA\u201915, CEUR Workshop Proceedings, vol. 1509. CEUR-WS.org (2015). http:\/\/ceur-ws.org\/Vol-1509\/ITALIA2015_paper_4.pdf"},{"key":"339_CR13","doi-asserted-by":"publisher","DOI":"10.1045\/july2017-beel","author":"J Beel","year":"2017","unstructured":"Beel, J., Carevic, Z., Schaible, J., Neusch, G.: RARD: the related-article recommendation dataset. D Lib Mag. (2017). https:\/\/doi.org\/10.1045\/july2017-beel","journal-title":"D Lib Mag."},{"key":"339_CR14","doi-asserted-by":"publisher","unstructured":"Beel, J., Collins, A., Kopp, O., Dietz, L.W., Knoth, P.: Online Evaluations for Everyone: Mr. DLib\u2019s Living Lab for Scholarly Recommendations. In: ECIR\u201919, LNCS, 11438, 213\u2013219. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-15719-7_27","DOI":"10.1007\/978-3-030-15719-7_27"},{"key":"339_CR15","doi-asserted-by":"publisher","unstructured":"Beel, J., Dinesh, S., Mayr, P., Carevic, Z., Jain, R.: Stereotype and most-popular recommendations in the digital library Sowiport. In: ISI\u201917, Schriften zur Informationswissenschaft, 70, 96\u2013108. Verlag Werner H\u00fclsbusch (2017). https:\/\/doi.org\/10.18452\/1441","DOI":"10.18452\/1441"},{"issue":"4","key":"339_CR16","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s00799-015-0156-0","volume":"17","author":"J Beel","year":"2016","unstructured":"Beel, J., Gipp, B., Langer, S., Breitinger, C.: Research-paper recommender systems: a literature survey. Int. J. Digit. Libr. 17(4), 305\u2013338 (2016). https:\/\/doi.org\/10.1007\/s00799-015-0156-0","journal-title":"Int. J. Digit. Libr."},{"key":"339_CR17","doi-asserted-by":"publisher","unstructured":"Beel, J., Langer, S.: A Comparison of offline evaluations, online evaluations, and user studies in the context of research-paper recommender systems. In: TPDL\u201915, LNCS, 9316, 153\u2013168. Springer (2015). https:\/\/doi.org\/10.1007\/978-3-319-24592-8_12","DOI":"10.1007\/978-3-319-24592-8_12"},{"issue":"3","key":"339_CR18","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/s00799-019-00270-7","volume":"21","author":"F Beierle","year":"2020","unstructured":"Beierle, F., Aizawa, A., Collins, A., Beel, J.: Choice overload and recommendation effectiveness in related-article recommendations. Int. J. Digit. Libr. 21(3), 231\u2013246 (2020). https:\/\/doi.org\/10.1007\/s00799-019-00270-7","journal-title":"Int. J. Digit. Libr."},{"key":"339_CR19","unstructured":"Bereczki, M.: Graph neural networks for article recommendation based on implicit user feedback and content. Master\u2019s thesis, KTH, School of Electrical Engineering and Computer Science (EECS) (2021)"},{"key":"339_CR20","doi-asserted-by":"publisher","unstructured":"Bogers, T., van\u00a0den Bosch, A.: recommending scientific articles using citeulike. In: RecSys\u201908, pp. 287\u2013290. ACM (2008). https:\/\/doi.org\/10.1145\/1454008.1454053","DOI":"10.1145\/1454008.1454053"},{"key":"339_CR21","doi-asserted-by":"publisher","unstructured":"Bulut, B., G\u00fcndo\u011fan, E., Kaya, B., Alhajj, R., Kaya, M.: User\u2019s research interests based paper recommendation system: a deep learning approach. pp. 117\u2013130. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-33698-1_7","DOI":"10.1007\/978-3-030-33698-1_7"},{"key":"339_CR22","doi-asserted-by":"publisher","unstructured":"Bulut, B., Kaya, B., Kaya, M.: A paper recommendation system based on user interest and citations. In: UBMYK\u201919, pp. 1\u20135 (2019). https:\/\/doi.org\/10.1109\/UBMYK48245.2019.8965533","DOI":"10.1109\/UBMYK48245.2019.8965533"},{"issue":"2","key":"339_CR23","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1007\/s10115-018-1324-5","volume":"61","author":"ZD Champiri","year":"2019","unstructured":"Champiri, Z.D., Asemi, A., Salim, S.S.B.: Meta-analysis of evaluation methods and metrics used in context-aware scholarly recommender systems. Knowl. Inf. Syst. 61(2), 1147\u20131178 (2019). https:\/\/doi.org\/10.1007\/s10115-018-1324-5","journal-title":"Knowl. Inf. Syst."},{"key":"339_CR24","unstructured":"Chaudhuri, A., Samanta, D., Sarma, M.: Modeling user behaviour in research paper recommendation system (2021). arXiv:2107.07831"},{"key":"339_CR25","doi-asserted-by":"publisher","unstructured":"Chaudhuri, A., Sarma, M., Samanta, D.: Advanced feature identification towards research article recommendation: a machine learning based approach. In: TENCON\u201919, pp. 7\u201312. IEEE (2019). https:\/\/doi.org\/10.1109\/TENCON.2019.8929386","DOI":"10.1109\/TENCON.2019.8929386"},{"issue":"2","key":"339_CR26","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1007\/s00799-021-00301-2","volume":"22","author":"A Chaudhuri","year":"2021","unstructured":"Chaudhuri, A., Sinhababu, N., Sarma, M., Samanta, D.: Hidden features identification for designing an efficient research article recommendation system. Int. J. Digit. Libr. 22(2), 233\u2013249 (2021). https:\/\/doi.org\/10.1007\/s00799-021-00301-2","journal-title":"Int. J. Digit. Libr."},{"key":"339_CR27","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/978-981-32-9298-7_14","volume-title":"Academic Paper Recommendation Based on Clustering and Pattern Matching","author":"J Chen","year":"2019","unstructured":"Chen, J., Ban, Z.: Academic Paper Recommendation Based on Clustering and Pattern Matching, pp. 171\u2013182. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-981-32-9298-7_14"},{"key":"339_CR28","doi-asserted-by":"publisher","unstructured":"Collins, A., Beel, J.: Document embeddings vs. keyphrases vs. terms for recommender systems: a large-scale online evaluation. In: JCDL\u201919, pp. 130\u2013133. IEEE (2019). https:\/\/doi.org\/10.1109\/JCDL.2019.00027","DOI":"10.1109\/JCDL.2019.00027"},{"key":"339_CR29","doi-asserted-by":"publisher","unstructured":"Du, N., Guo, J., Wu, C.Q., Hou, A., Zhao, Z., Gan, D.: Recommendation of academic papers based on heterogeneous information networks. In: AICCSA\u201920, pp. 1\u20136. IEEE (2020). https:\/\/doi.org\/10.1109\/AICCSA50499.2020.9316516","DOI":"10.1109\/AICCSA50499.2020.9316516"},{"issue":"6","key":"339_CR30","doi-asserted-by":"publisher","first-page":"2709","DOI":"10.1109\/TKDE.2019.2953721","volume":"33","author":"Z Du","year":"2021","unstructured":"Du, Z., Tang, J., Ding, Y.: POLAR++: active one-shot personalized article recommendation. IEEE Trans. Knowl. Data Eng. 33(6), 2709\u20132722 (2021). https:\/\/doi.org\/10.1109\/TKDE.2019.2953721","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"339_CR31","doi-asserted-by":"crossref","unstructured":"Ekstrand, M.D., Das, A., Burke, R., Diaz, F.: Fairness and discrimination in information access systems (2021). arXiv:2105.05779","DOI":"10.1561\/9781638280415"},{"issue":"4","key":"339_CR32","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s00799-020-00288-2","volume":"21","author":"M F\u00e4rber","year":"2020","unstructured":"F\u00e4rber, M., Jatowt, A.: Citation recommendation: approaches and datasets. Int. J. Digit. Libr. 21(4), 375\u2013405 (2020). https:\/\/doi.org\/10.1007\/s00799-020-00288-2","journal-title":"Int. J. Digit. Libr."},{"issue":"2","key":"339_CR33","doi-asserted-by":"publisher","first-page":"459","DOI":"10.13052\/jwe1540-9589.20210","volume":"20","author":"S Feng","year":"2021","unstructured":"Feng, S., Meng, J., Zhang, J.: News recommendation systems in the era of information overload. J. Web Eng. 20(2), 459\u2013470 (2021). https:\/\/doi.org\/10.13052\/jwe1540-9589.20210","journal-title":"J. Web Eng."},{"key":"339_CR34","unstructured":"Garfield, E.: Can citation indexing be automated? (1964)"},{"key":"339_CR35","doi-asserted-by":"publisher","unstructured":"Giles, C.L., Bollacker, K.D., Lawrence, S.: CiteSeer: an automatic citation indexing system. In: ACM DL\u201998, pp. 89\u201398. ACM (1998). https:\/\/doi.org\/10.1145\/276675.276685","DOI":"10.1145\/276675.276685"},{"key":"339_CR36","doi-asserted-by":"publisher","unstructured":"Gingstad, K., Jekteberg, \u00d8., Balog, K.: ArXivDigest: a living lab for personalized scientific literature recommendation. In: CIKM\u201920, pp. 3393\u20133396. ACM (2020). https:\/\/doi.org\/10.1145\/3340531.3417417","DOI":"10.1145\/3340531.3417417"},{"key":"339_CR37","doi-asserted-by":"crossref","unstructured":"Guo, G., Chen, B., Zhang, X., Liu, Z., Dong, Z., He, X.: Leveraging title-abstract attentive semantics for paper recommendation. In: IAAI\u201920, pp. 67\u201374. AAAI Press (2020). https:\/\/aaai.org\/ojs\/index.php\/AAAI\/article\/view\/5335","DOI":"10.1609\/aaai.v34i01.5335"},{"issue":"2","key":"339_CR38","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/s11192-019-03053-8","volume":"119","author":"R Habib","year":"2019","unstructured":"Habib, R., Afzal, M.T.: Sections-based bibliographic coupling for research paper recommendation. Scientometrics 119(2), 643\u2013656 (2019). https:\/\/doi.org\/10.1007\/s11192-019-03053-8","journal-title":"Scientometrics"},{"issue":"1","key":"339_CR39","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s11192-020-03642-y","volume":"125","author":"K Haruna","year":"2020","unstructured":"Haruna, K., Ismail, M.A., Qazi, A., Kakudi, H.A., Hassan, M., Muaz, S.A., Chiroma, H.: Research paper recommender system based on public contextual metadata. Scientometrics 125(1), 101\u2013114 (2020). https:\/\/doi.org\/10.1007\/s11192-020-03642-y","journal-title":"Scientometrics"},{"key":"339_CR40","doi-asserted-by":"publisher","DOI":"10.1045\/march2015-hienert","author":"D Hienert","year":"2015","unstructured":"Hienert, D., Sawitzki, F., Mayr, P.: Digital library research in action: supporting information retrieval in sowiport. D Lib. Mag. (2015). https:\/\/doi.org\/10.1045\/march2015-hienert","journal-title":"D Lib. Mag."},{"key":"339_CR41","doi-asserted-by":"publisher","unstructured":"Hu, D., Ma, H., Liu, Y., He, X.: Scientific paper recommendation using author\u2019s dual role citation relationship. In: Intelligent information processing\u201920, IFIP advances in information and communication technology. 581, 121\u2013132. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-46931-3_12","DOI":"10.1007\/978-3-030-46931-3_12"},{"key":"339_CR42","doi-asserted-by":"publisher","unstructured":"Hua, S., Chen, W., Li, Z., Zhao, P., Zhao, L.: Path-Based Academic Paper Recommendation. In: WISE\u201920, LNCS, 12343, 343\u2013356. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-62008-0_24","DOI":"10.1007\/978-3-030-62008-0_24"},{"key":"339_CR43","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1016\/j.future.2021.06.007","volume":"125","author":"Z Ji","year":"2021","unstructured":"Ji, Z., Wu, M., Yang, H., Armend\u00e1riz-I\u00f1igo, J.E.: Temporal sensitive heterogeneous graph neural network for news recommendation. Future Gener. Comput. Syst. 125, 324\u2013333 (2021). https:\/\/doi.org\/10.1016\/j.future.2021.06.007","journal-title":"Future Gener. Comput. Syst."},{"key":"339_CR44","doi-asserted-by":"publisher","unstructured":"Jing, S., Yu, S.: Research of paper recommendation system based on citation network model. In: ML4CS\u201920, LNCS, 12488, 237\u2013247. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-62463-7_22","DOI":"10.1007\/978-3-030-62463-7_22"},{"key":"339_CR45","doi-asserted-by":"crossref","unstructured":"Kanakia, A., Shen, Z., Eide, D., Wang, K.: A Scalable hybrid research paper recommender system for microsoft academic (2019). arXiv:1905.08880","DOI":"10.1145\/3308558.3313700"},{"issue":"8","key":"339_CR46","doi-asserted-by":"publisher","first-page":"1222","DOI":"10.1587\/transinf.2020BDP0008","volume":"E104D","author":"Y Kang","year":"2021","unstructured":"Kang, Y., Hou, A., Zhao, Z., Gan, D.: A hybrid approach for paper recommendation. IEICE Trans. Inform. Syst. E104D(8), 1222\u20131231 (2021). https:\/\/doi.org\/10.1587\/transinf.2020BDP0008","journal-title":"IEICE Trans. Inform. Syst."},{"key":"339_CR47","unstructured":"Keller, J., Munz, L.P.M.: TEKMA at CLEF-2021: BM-25 based rankings for scientific publication retrieval and data set recommendation. In: CLEF\u201921, CEUR Workshop Proceedings. 2936, 1700\u20131711. CEUR-WS.org (2021). http:\/\/ceur-ws.org\/Vol-2936\/paper-144.pdf"},{"issue":"1","key":"339_CR48","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1109\/TETC.2018.2830698","volume":"9","author":"X Kong","year":"2021","unstructured":"Kong, X., Mao, M., Wang, W., Liu, J., Xu, B.: VOPRec: vector representation learning of papers with text information and structural identity for recommendation. IEEE Trans. Emerg. Top. Comput. 9(1), 226\u2013237 (2021). https:\/\/doi.org\/10.1109\/TETC.2018.2830698","journal-title":"IEEE Trans. Emerg. Top. Comput."},{"key":"339_CR49","doi-asserted-by":"publisher","unstructured":"L, H., Liu, S., Pan, L.: Paper recommendation based on author-paper interest and graph structure. In: CSCWD\u201921, pp. 256\u2013261. IEEE (2021). https:\/\/doi.org\/10.1109\/CSCWD49262.2021.9437743","DOI":"10.1109\/CSCWD49262.2021.9437743"},{"key":"339_CR50","unstructured":"Le, M., Kayal, S., Douglas, A.: The impact of recommenders on scientific article discovery: the case of mendeley suggest. In: ImpactRS@RecSys\u201919, CEUR Workshop Proceedings, vol. 2462. CEUR-WS.org (2019). http:\/\/ceur-ws.org\/Vol-2462\/paper5.pdf"},{"key":"339_CR51","unstructured":"Lee, B.C.G., Lo, K., Downey, D., Weld, D.S.: Explanation-based tuning of opaque machine learners with application to paper recommendation (2020). arXiv:2003.04315"},{"key":"339_CR52","unstructured":"Lee, J., Lee, K., Kim, J.G.: Personalized academic research paper recommendation system (2013). arXiv:1304.5457"},{"key":"339_CR53","doi-asserted-by":"publisher","unstructured":"Leskovec, J., Kleinberg, J.M., Faloutsos, C.: Graphs over time: densification laws, shrinking diameters and possible explanations. In: SIGKDD\u201905, pp. 177\u2013187. ACM (2005). https:\/\/doi.org\/10.1145\/1081870.1081893","DOI":"10.1145\/1081870.1081893"},{"issue":"2","key":"339_CR54","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.14778\/1687553.1687577","volume":"2","author":"M Ley","year":"2009","unstructured":"Ley, M.: DBLP: some lessons learned. Proc VLDB Endow. 2(2), 1493\u20131500 (2009). https:\/\/doi.org\/10.14778\/1687553.1687577","journal-title":"Proc VLDB Endow."},{"key":"339_CR55","doi-asserted-by":"publisher","unstructured":"Li, W., Chang, C., He, C., Wu, Z., Guo, J., Peng, B.: Academic paper recommendation method combining heterogeneous network and temporal attributes. In: Chinese CSCW\u201921, pp. 456\u2013468. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-16-2540-4_33","DOI":"10.1007\/978-981-16-2540-4_33"},{"issue":"3","key":"339_CR56","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3312528","volume":"37","author":"X Li","year":"2019","unstructured":"Li, X., Chen, Y., Pettit, B., de Rijke, M.: Personalised reranking of paper recommendations using paper content and user behavior. ACM Trans. Inform. Syst. 37(3), 1\u201323 (2019). https:\/\/doi.org\/10.1145\/3312528","journal-title":"ACM Trans. Inform. Syst."},{"key":"339_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2021.113546","volume":"146","author":"Y Li","year":"2021","unstructured":"Li, Y., Wang, R., Nan, G., Li, D., Li, M.: A personalized paper recommendation method considering diverse user preferences. Decis. Support Syst. 146, 113546 (2021). https:\/\/doi.org\/10.1016\/j.dss.2021.113546","journal-title":"Decis. Support Syst."},{"issue":"1","key":"339_CR58","doi-asserted-by":"publisher","first-page":"33","DOI":"10.5539\/cis.v12n1p33","volume":"12","author":"Z Li","year":"2019","unstructured":"Li, Z., Zou, X.: A review on personalized academic paper recommendation. Comput. Inf. Sci. 12(1), 33\u201343 (2019). https:\/\/doi.org\/10.5539\/cis.v12n1p33","journal-title":"Comput. Inf. Sci."},{"key":"339_CR59","doi-asserted-by":"publisher","unstructured":"Lin, S.j., Lee, G., Peng, S.L.: Academic article recommendation by considering the research field trajectory. pp. 447\u2013454. Springer (2021). https:\/\/doi.org\/10.1007\/978-3-030-65407-8_39","DOI":"10.1007\/978-3-030-65407-8_39"},{"key":"339_CR60","doi-asserted-by":"publisher","unstructured":"Liu, H., Kou, H., Chi, X., Qi, L.: Combining time, keywords and authors information to construct papers correlation graph (S). In: SEKE\u201919, pp. 11\u201319. KSI Research Inc. and Knowledge Systems Institute Graduate School (2019). https:\/\/doi.org\/10.18293\/SEKE2019-161","DOI":"10.18293\/SEKE2019-161"},{"key":"339_CR61","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/2085638","author":"H Liu","year":"2020","unstructured":"Liu, H., Kou, H., Yan, C., Qi, L.: Keywords-driven and popularity-aware paper recommendation based on undirected paper citation graph. Complex (2020). https:\/\/doi.org\/10.1155\/2020\/2085638","journal-title":"Complex"},{"key":"339_CR62","doi-asserted-by":"publisher","unstructured":"Lu, Y., He, Y., Cai, Y., Peng, Z., Tang, Y.: Time-aware neural collaborative filtering with multi-dimensional features on academic paper recommendation. In: CSCWD\u201921, pp. 1052\u20131057. IEEE (2021). https:\/\/doi.org\/10.1109\/CSCWD49262.2021.9437673","DOI":"10.1109\/CSCWD49262.2021.9437673"},{"key":"339_CR63","doi-asserted-by":"publisher","first-page":"79887","DOI":"10.1109\/ACCESS.2019.2923293","volume":"7","author":"X Ma","year":"2019","unstructured":"Ma, X., Wang, R.: Personalized scientific paper recommendation based on heterogeneous graph representation. IEEE Access 7, 79887\u201379894 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2923293","journal-title":"IEEE Access"},{"issue":"1","key":"339_CR64","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1007\/s11036-018-1133-9","volume":"24","author":"X Ma","year":"2019","unstructured":"Ma, X., Zhang, Y., Zeng, J.: Newly published scientific papers recommendation in heterogeneous information networks. Mob. Networks Appl. 24(1), 69\u201379 (2019). https:\/\/doi.org\/10.1007\/s11036-018-1133-9","journal-title":"Mob. Networks Appl."},{"issue":"2","key":"339_CR65","doi-asserted-by":"publisher","first-page":"24","DOI":"10.4018\/IJIIT.2020040102","volume":"16","author":"G Manju","year":"2020","unstructured":"Manju, G., Abhinaya, P., Hemalatha, M.R., Manju, G.G., Manju, G.G.: Cold start problem alleviation in a research paper recommendation system using the random walk approach on a heterogeneous user-paper graph. Int. J. Intell. Inf. Technol. 16(2), 24\u201348 (2020). https:\/\/doi.org\/10.4018\/IJIIT.2020040102","journal-title":"Int. J. Intell. Inf. Technol."},{"key":"339_CR66","doi-asserted-by":"publisher","unstructured":"McInerney, J., Lacker, B., Hansen, S., Higley, K., Bouchard, H., Gruson, A., Mehrotra, R.: Explore, exploit, and explain: personalizing explainable recommendations with bandits. In: RecSys\u201918, pp. 31\u201339. ACM (2018). https:\/\/doi.org\/10.1145\/3240323.3240354","DOI":"10.1145\/3240323.3240354"},{"issue":"3","key":"339_CR67","first-page":"183","volume":"28","author":"Z Medic","year":"2020","unstructured":"Medic, Z., Snajder, J.: A survey of citation recommendation tasks and methods. J. Comput. Inf. Technol. 28(3), 183\u2013205 (2020)","journal-title":"J. Comput. Inf. Technol."},{"key":"339_CR68","unstructured":"Mohamed\u00a0Hassan, H.A., Sansonetti, G., Gasparetti, F., Micarelli, A., Beel, J.: BERT, ELMo, USE and InferSent sentence encoders: the panacea for research-paper recommendation? In: RecSys\u201919, CEUR Workshop Proceedings. 2431, 6\u201310. CEUR-WS.org (2019). http:\/\/ceur-ws.org\/Vol-2431\/paper2.pdf"},{"key":"339_CR69","unstructured":"Mohamed Hassan, H.A., Sansonetti, G., Micarelli, A.: Tag-aware document representation for research paper recommendation (2020). https:\/\/www.researchgate.net\/publication\/343319230_Tag-Aware_Document_Representation_for_Research_Paper_Recommendation"},{"key":"339_CR70","unstructured":"Moskalenko, O., S\u00e1ez-Trumper, D., Parra, D.: Scalable recommendation of wikipedia articles to editors using representation learning. In: RecSys\u201920, CEUR workshop proceedings. 2697. CEUR-WS.org (2020). http:\/\/ceur-ws.org\/Vol-2697\/paper1_complexrec.pdf"},{"key":"339_CR71","doi-asserted-by":"publisher","unstructured":"Nair, A.M., Benny, O., George, J.: Content based scientific article recommendation system using deep learning technique. In: Inventive systems and control, pp. 965\u2013977. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-16-1395-1_70","DOI":"10.1007\/978-981-16-1395-1_70"},{"key":"339_CR72","doi-asserted-by":"publisher","unstructured":"Ng, Y.: Research paper recommendation based on content similarity, peer reviews, authority, and popularity. In: ICTAI\u201920, pp. 47\u201352. IEEE (2020). https:\/\/doi.org\/10.1109\/ICTAI50040.2020.00018","DOI":"10.1109\/ICTAI50040.2020.00018"},{"issue":"2","key":"339_CR73","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1504\/IJBIDM.2020.104738","volume":"16","author":"YK Ng","year":"2020","unstructured":"Ng, Y.K.: CBRec: a book recommendation system for children using the matrix factorisation and content-based filtering approaches. Int. J. Bus. Intell. Data Mining 16(2), 129\u2013149 (2020). https:\/\/doi.org\/10.1504\/IJBIDM.2020.104738","journal-title":"Int. J. Bus. Intell. Data Mining"},{"key":"339_CR74","doi-asserted-by":"publisher","unstructured":"Nishioka, C., Hauke, J., Scherp, A.: Research paper recommender system with serendipity using tweets vs. diversification. In: ICADL\u201919, LNCS. 11853, 63\u201370. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-34058-2_7","DOI":"10.1007\/978-3-030-34058-2_7"},{"key":"339_CR75","doi-asserted-by":"publisher","unstructured":"Nishioka, C., Hauke, J., Scherp, A.: Towards serendipitous research paper recommender using tweets and diversification. In: TPDL\u201919, LNCS. 11799, 339\u2013343. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-30760-8_29","DOI":"10.1007\/978-3-030-30760-8_29"},{"key":"339_CR76","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.273","volume":"6","author":"C Nishioka","year":"2020","unstructured":"Nishioka, C., Hauke, J., Scherp, A.: Influence of tweets and diversification on serendipitous research paper recommender systems. PeerJ Comput. Sci. 6, e273 (2020). https:\/\/doi.org\/10.7717\/peerj-cs.273","journal-title":"PeerJ Comput. Sci."},{"key":"339_CR77","unstructured":"Ostendorff, M.: Contextual document similarity for content-based literature recommender systems (2020). arXiv:2008.00202"},{"key":"339_CR78","doi-asserted-by":"crossref","unstructured":"Ostendorff, M., Breitinger, C., Gipp, B.: A qualitative evaluation of user preference for link-based vs. text-based recommendations of wikipedia articles (2021). arXiv:2109.07791","DOI":"10.1007\/978-3-030-91669-5_6"},{"key":"339_CR79","doi-asserted-by":"crossref","unstructured":"Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A., Brennan, S.E., Chou, R., Glanville, J., Grimshaw, J.M., Hr\u00f3bjartsson, A., Lalu, M.M., Li, T., Loder, E.W., Mayo-Wilson, E., McDonald, S., McGuinness, L.A., Stewart, L.A., Thomas, J., Tricco, A.C., Welch, V.A., Whiting, P., Moher, D.: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372 (2021). https:\/\/www.bmj.com\/content\/372\/bmj.n71","DOI":"10.1136\/bmj.n71"},{"key":"339_CR80","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103399","volume":"104","author":"BG Patra","year":"2020","unstructured":"Patra, B.G., Maroufy, V., Soltanalizadeh, B., Deng, N., Zheng, W.J., Roberts, K., Wu, H.: A content-based literature recommendation system for datasets to improve data reusability: a case study on gene expression omnibus (geo) datasets. J. Biomed. Inform. 104, 103399 (2020). https:\/\/doi.org\/10.1016\/j.jbi.2020.103399","journal-title":"J. Biomed. Inform."},{"key":"339_CR81","doi-asserted-by":"publisher","DOI":"10.1002\/asi.23394","author":"DR Radev","year":"2009","unstructured":"Radev, D.R., Joseph, M.T., Gibson, B., Muthukrishnan, P.: A bibliometric and network analysis of the field of computational linguistics. J. Am. Soc. Inform. Sci. Technol. (2009). https:\/\/doi.org\/10.1002\/asi.23394","journal-title":"J. Am. Soc. Inform. Sci. Technol."},{"key":"339_CR82","doi-asserted-by":"publisher","unstructured":"Radev, D.R., Muthukrishnan, P., Qazvinian, V.: The ACL anthology network corpus. In: NLPIR4DL\u201909 (2009). https:\/\/doi.org\/10.5555\/1699750.1699759","DOI":"10.5555\/1699750.1699759"},{"key":"339_CR83","doi-asserted-by":"publisher","DOI":"10.1007\/s10579-012-9211-2","author":"DR Radev","year":"2013","unstructured":"Radev, D.R., Muthukrishnan, P., Qazvinian, V., Abu-Jbara, A.: The ACL anthology network corpus. Lang. Resour. Eval. (2013). https:\/\/doi.org\/10.1007\/s10579-012-9211-2","journal-title":"Lang. Resour. Eval."},{"key":"339_CR84","doi-asserted-by":"publisher","unstructured":"Rahdari, B., Brusilovsky, P.: User-controlled hybrid recommendation for academic papers. In: IUI Companion\u201919, pp. 99\u2013100. ACM (2019). https:\/\/doi.org\/10.1145\/3308557.3308717","DOI":"10.1145\/3308557.3308717"},{"key":"339_CR85","doi-asserted-by":"publisher","unstructured":"Rahdari, B., Brusilovsky, P., Thaker, K., Barria-Pineda, J.: Knowledge-driven wikipedia article recommendation for electronic textbooks. In: EC-TEL\u201920, LNCS. 12315, 363\u2013368. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-57717-9_28","DOI":"10.1007\/978-3-030-57717-9_28"},{"key":"339_CR86","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-8530-2_13","author":"S Renuka","year":"2021","unstructured":"Renuka, S., Raj Kiran, G.S.S., Rohit, P.: An unsupervised content-based article recommendation system using natural language processing. Data Intell. Cogn. Inform. (2021). https:\/\/doi.org\/10.1007\/978-981-15-8530-2_13","journal-title":"Data Intell. Cogn. Inform."},{"key":"339_CR87","doi-asserted-by":"publisher","unstructured":"Safaryan, A., Filchenkov, P., Yan, W., Kutuzov, A., Nikishina, I.: Semantic recommendation system for bilingual corpus of academic papers. In: AIST\u201920, Communications in Computer and Information Science. 1357, 22\u201336. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-71214-3_3","DOI":"10.1007\/978-3-030-71214-3_3"},{"key":"339_CR88","doi-asserted-by":"publisher","first-page":"83080","DOI":"10.1109\/ACCESS.2021.3086964","volume":"9","author":"N Sakib","year":"2021","unstructured":"Sakib, N., Ahmad, R.B., Ahsan, M., Based, M.A., Haruna, K., Haider, J., Gurusamy, S.: A hybrid personalized scientific paper recommendation approach integrating public contextual metadata. IEEE Access 9, 83080\u201383091 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3086964","journal-title":"IEEE Access"},{"key":"339_CR89","doi-asserted-by":"publisher","first-page":"51246","DOI":"10.1109\/ACCESS.2020.2980589","volume":"8","author":"N Sakib","year":"2020","unstructured":"Sakib, N., Ahmad, R.B., Haruna, K.: A collaborative approach toward scientific paper recommendation using citation context. IEEE Access 8, 51246\u201351255 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2980589","journal-title":"IEEE Access"},{"issue":"19","key":"339_CR90","doi-asserted-by":"publisher","DOI":"10.4108\/eai.13-6-2019.159121","volume":"6","author":"A Samad","year":"2019","unstructured":"Samad, A., Islam, M.A., Iqbal, M.A., Aleem, M.: Centrality-based paper citation recommender system. EAI Endorsed Trans. Ind. Networks Intell. Syst. 6(19), e2 (2019). https:\/\/doi.org\/10.4108\/eai.13-6-2019.159121","journal-title":"EAI Endorsed Trans. Ind. Networks Intell. Syst."},{"key":"339_CR91","doi-asserted-by":"crossref","unstructured":"Schaer, P., Breuer, T., Castro, L.J., Wolff, B., Schaible, J., Tavakolpoursaleh, N.: Overview of LiLAS 2021\u2014living labs for academic search (extended overview). In: CLEF\u201921, CEUR Workshop Proceedings. 2936, 1668\u20131699. CEUR-WS.org (2021). http:\/\/ceur-ws.org\/Vol-2936\/paper-143.pdf","DOI":"10.1007\/978-3-030-85251-1_25"},{"issue":"3","key":"339_CR92","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1007\/s11227-019-03009-y","volume":"76","author":"A Shahid","year":"2020","unstructured":"Shahid, A., Afzal, M.T., Abdar, M., Basiri, M.E., Zhou, X., Yen, N.Y., Chang, J.: Insights into relevant knowledge extraction techniques: a comprehensive review. J. Supercomput. 76(3), 1695\u20131733 (2020). https:\/\/doi.org\/10.1007\/s11227-019-03009-y","journal-title":"J. Supercomput."},{"key":"339_CR93","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.524","volume":"7","author":"A Shahid","year":"2021","unstructured":"Shahid, A., Afzal, M.T., Alharbi, A., Aljuaid, H., Al-Otaibi, S.: In-text citation\u2019s frequencies-based recommendations of relevant research papers. PeerJ Comput. Sci. 7, e524 (2021). https:\/\/doi.org\/10.7717\/peerj-cs.524","journal-title":"PeerJ Comput. Sci."},{"issue":"3","key":"339_CR94","doi-asserted-by":"publisher","first-page":"3121","DOI":"10.32604\/cmc.2021.013809","volume":"66","author":"A Shahid","year":"2021","unstructured":"Shahid, A., Afzal, M.T., Saleem, M.Q., Idrees, M.S.E., Omer, M.K.: Extension of direct citation model using in-text citations. Comput. Mater. Continua 66(3), 3121\u20133138 (2021). https:\/\/doi.org\/10.32604\/cmc.2021.013809","journal-title":"Comput. Mater. Continua"},{"issue":"3","key":"339_CR95","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1093\/jamiaopen\/ooaa028","volume":"3","author":"B Sharma","year":"2020","unstructured":"Sharma, B., Willis, V.C., Huettner, C.S., Beaty, K., Snowdon, J.L., Xue, S., South, B.R., Jackson, G.P., Weeraratne, D., Michelini, V.: Predictive article recommendation using natural language processing and machine learning to support evidence updates in domain-specific knowledge graphs. JAMIA Open 3(3), 332\u2013337 (2020). https:\/\/doi.org\/10.1093\/jamiaopen\/ooaa028","journal-title":"JAMIA Open"},{"key":"339_CR96","doi-asserted-by":"publisher","unstructured":"Shi, H., Ma, W., Zhang, X., Jiang, J., Liu, Y., Chen, S.: A hybrid paper recommendation method by using heterogeneous graph and metadata. In: IJCNN\u201920, pp. 1\u20138. IEEE (2020). https:\/\/doi.org\/10.1109\/IJCNN48605.2020.9206733","DOI":"10.1109\/IJCNN48605.2020.9206733"},{"key":"339_CR97","doi-asserted-by":"publisher","unstructured":"Sinha, A., Shen, Z., Song, Y., Ma, H., Eide, D., Hsu, B.P., Wang, K.: An overview of microsoft academic service (MAS) and applications. In: WWW\u201915, pp. 243\u2013246. ACM (2015). https:\/\/doi.org\/10.1145\/2740908.2742839","DOI":"10.1145\/2740908.2742839"},{"key":"339_CR98","doi-asserted-by":"publisher","unstructured":"Subathra, P., Kumar, P.N.: Recommending research article based on user queries using latent dirichlet allocation. in: soft computing and signal processing, pp. 163\u2013175. Springer Singapore (2020). https:\/\/doi.org\/10.1007\/978-981-15-2475-2_15","DOI":"10.1007\/978-981-15-2475-2_15"},{"key":"339_CR99","doi-asserted-by":"publisher","unstructured":"Sugiyama, K., Kan, M.: Scholarly paper recommendation via user\u2019s recent research interests. In: JCDL\u201910, pp. 29\u201338. ACM (2010). https:\/\/doi.org\/10.1145\/1816123.1816129","DOI":"10.1145\/1816123.1816129"},{"key":"339_CR100","doi-asserted-by":"publisher","unstructured":"Sugiyama, K., Kan, M.: Serendipitous recommendation for scholarly papers considering relations among researchers. In: JCDL\u201911, pp. 307\u2013310. ACM (2011). https:\/\/doi.org\/10.1145\/1998076.1998133","DOI":"10.1145\/1998076.1998133"},{"key":"339_CR101","doi-asserted-by":"publisher","unstructured":"Sugiyama, K., Kan, M.: Exploiting potential citation papers in scholarly paper recommendation. In: JCDL\u201913, pp. 153\u2013162. ACM (2013). https:\/\/doi.org\/10.1145\/2467696.2467701","DOI":"10.1145\/2467696.2467701"},{"issue":"2","key":"339_CR102","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/s00799-014-0122-2","volume":"16","author":"K Sugiyama","year":"2015","unstructured":"Sugiyama, K., Kan, M.: A comprehensive evaluation of scholarly paper recommendation using potential citation papers. Int. J. Digit. Libr. 16(2), 91\u2013109 (2015). https:\/\/doi.org\/10.1007\/s00799-014-0122-2","journal-title":"Int. J. Digit. Libr."},{"key":"339_CR103","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115028","volume":"180","author":"P Symeonidis","year":"2021","unstructured":"Symeonidis, P., Kirjackaja, L., Zanker, M.: Session-based news recommendations using SimRank on multi-modal graphs. Expert Syst. Appl. 180, 115028 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2021.115028","journal-title":"Expert Syst. Appl."},{"key":"339_CR104","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.6227","author":"H Tang","year":"2021","unstructured":"Tang, H., Liu, B., Qian, J.: Content-based and knowledge graph-based paper recommendation: exploring user preferences with the knowledge graphs for scientific paper recommendation. Concurr. Comput. Pract. Exp. (2021). https:\/\/doi.org\/10.1002\/cpe.6227","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"339_CR105","doi-asserted-by":"publisher","unstructured":"Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., Su, Z.: ArnetMiner: extraction and mining of academic social networks. In: SIGKDD\u201908, pp. 990\u2013998. ACM (2008). https:\/\/doi.org\/10.1145\/1401890.1402008","DOI":"10.1145\/1401890.1402008"},{"key":"339_CR106","doi-asserted-by":"publisher","unstructured":"Tanner, W., Akbas, E., Hasan, M.: Paper recommendation based on citation relation. In: Big Data\u201919, pp. 3053\u20133059. IEEE (2019). https:\/\/doi.org\/10.1109\/BigData47090.2019.9006200","DOI":"10.1109\/BigData47090.2019.9006200"},{"key":"339_CR107","doi-asserted-by":"publisher","unstructured":"Tao, M., Yang, X., Gu, G., Li, B.: Paper recommend based on LDA and PageRank, pp. 571\u2013584. Springer (2020). https:\/\/doi.org\/10.1007\/978-981-15-8101-4_51","DOI":"10.1007\/978-981-15-8101-4_51"},{"key":"339_CR108","doi-asserted-by":"publisher","first-page":"33145","DOI":"10.1109\/ACCESS.2019.2900520","volume":"7","author":"W Waheed","year":"2019","unstructured":"Waheed, W., Imran, M., Raza, B., Malik, A.K., Khattak, H.A.: A hybrid approach toward research paper recommendation using centrality measures and author ranking. IEEE Access 7, 33145\u201333158 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2900520","journal-title":"IEEE Access"},{"key":"339_CR109","unstructured":"Wang, B., Weng, Z., Wang, Y.: A novel paper recommendation method empowered by knowledge graph: for research beginners (2021). arXiv:2103.08819"},{"key":"339_CR110","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107631","volume":"110","author":"G Wang","year":"2021","unstructured":"Wang, G., Wang, H., Yang, Y., Xu, D., Yang, J., Yue, F.: Group article recommendation based on ER rule in scientific social networks. Appl. Soft Comput. 110, 107631 (2021). https:\/\/doi.org\/10.1016\/j.asoc.2021.107631","journal-title":"Appl. Soft Comput."},{"key":"339_CR111","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2021.3072426","author":"G Wang","year":"2021","unstructured":"Wang, G., Zhang, X., Wang, H., Chu, Y., Shao, Z.: Group-oriented paper recommendation with probabilistic matrix factorization and evidential reasoning in scientific social network. IEEE Trans. Syst. Man Cybern. Syst. (2021). https:\/\/doi.org\/10.1109\/TSMC.2021.3072426","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"339_CR112","unstructured":"Wang, H., Chen, B., Li, W.: Collaborative topic regression with social regularization for tag recommendation. In: IJCAI\u201913, pp. 2719\u20132725. IJCAI\/AAAI (2013). http:\/\/www.aaai.org\/ocs\/index.php\/IJCAI\/IJCAI13\/paper\/view\/7006"},{"key":"339_CR113","doi-asserted-by":"publisher","unstructured":"Wang, X., Xu, H., Tan, W., Wang, Z., Xu, X.: Scholarly paper recommendation via related path analysis in knowledge graph. In: ICSS\u201920, pp. 36\u201343. IEEE (2020). https:\/\/doi.org\/10.1109\/ICSS50103.2020.00014","DOI":"10.1109\/ICSS50103.2020.00014"},{"key":"339_CR114","doi-asserted-by":"publisher","unstructured":"Wu, J., Kim, K., Giles, C.L.: CiteSeerX: 20 years of service to scholarly big data. In: AIDR\u201919, pp. 1:1\u20131:4. ACM (2019). https:\/\/doi.org\/10.1145\/3359115.3359119","DOI":"10.1145\/3359115.3359119"},{"key":"339_CR115","doi-asserted-by":"publisher","unstructured":"Xie, Y., Sun, Y., Bertino, E.: Learning domain semantics and cross-domain correlations for paper recommendation. In: SIGIR\u201921, pp. 706\u2013715. ACM (2021). https:\/\/doi.org\/10.1145\/3404835.3462975","DOI":"10.1145\/3404835.3462975"},{"key":"339_CR116","doi-asserted-by":"publisher","unstructured":"Xie, Y., Wang, S., Pan, W., Tang, H., Sun, Y.: Embedding based personalized new paper recommendation. In: Chinese CSCW\u201921, pp. 558\u2013570. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-16-2540-4_40","DOI":"10.1007\/978-981-16-2540-4_40"},{"issue":"6","key":"339_CR117","doi-asserted-by":"publisher","first-page":"2499","DOI":"10.1007\/s11280-019-00687-9","volume":"22","author":"Q Yang","year":"2019","unstructured":"Yang, Q., Li, Z., Liu, A., Liu, G., Zhao, L., Zhang, X., Zhang, M., Zhou, X.: A novel hybrid publication recommendation system using compound information. World Wide Web 22(6), 2499\u20132517 (2019). https:\/\/doi.org\/10.1007\/s11280-019-00687-9","journal-title":"World Wide Web"},{"key":"339_CR118","doi-asserted-by":"publisher","unstructured":"Yu, M., Hu, Y., Li, X., Zhao, M., Xu, T., Liu, H., Xu, L., Yu, R.: Paper recommendation with item-level collaborative memory network. In: KSEM\u201919, LNCS. 11775, 141\u2013152. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-29551-6_13","DOI":"10.1007\/978-3-030-29551-6_13"},{"key":"339_CR119","doi-asserted-by":"publisher","unstructured":"Zavrel, J., Grotov, A., Mitnik, J.: Building a platform for ensemble-based personalized research literature recommendations for AI and data science at zeta alpha. pp 536\u2013537. Association for Computing Machinery (2021). https:\/\/doi.org\/10.1145\/3460231.3474619","DOI":"10.1145\/3460231.3474619"},{"issue":"1","key":"339_CR120","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/1500000066","volume":"14","author":"Y Zhang","year":"2020","unstructured":"Zhang, Y., Chen, X.: Explainable recommendation: a survey and new perspectives. Found. Trends Inf. Retr. 14(1), 1\u2013101 (2020). https:\/\/doi.org\/10.1561\/1500000066","journal-title":"Found. Trends Inf. Retr."},{"issue":"2","key":"339_CR121","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1016\/j.joi.2019.03.013","volume":"13","author":"Y Zhang","year":"2019","unstructured":"Zhang, Y., Wang, M., Gottwalt, F., Saberi, M., Chang, E.: Ranking scientific articles based on bibliometric networks with a weighting scheme. J. Inform. 13(2), 616\u2013634 (2019). https:\/\/doi.org\/10.1016\/j.joi.2019.03.013","journal-title":"J. Inform."},{"key":"339_CR122","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Wang, M., Saberi, M., Chang, E.: Towards expert preference on academic article recommendation using bibliometric networks. In: PAKDD\u201920, pp. 11\u201319. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-60470-7_2","DOI":"10.1007\/978-3-030-60470-7_2"},{"key":"339_CR123","doi-asserted-by":"publisher","first-page":"188628","DOI":"10.1109\/ACCESS.2020.3031281","volume":"8","author":"X Zhao","year":"2020","unstructured":"Zhao, X., Kang, H., Feng, T., Meng, C., Nie, Z.: A hybrid model based on LFM and BiGRU toward research paper recommendation. IEEE Access 8, 188628\u2013188640 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.3031281","journal-title":"IEEE Access"},{"key":"339_CR124","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106744","volume":"215","author":"Y Zhu","year":"2021","unstructured":"Zhu, Y., Lin, Q., Lu, H., Shi, K., Qiu, P., Niu, Z.: Recommending scientific paper via heterogeneous knowledge embedding based attentive recurrent neural networks. Knowl. Based Syst. 215, 106744 (2021). https:\/\/doi.org\/10.1016\/j.knosys.2021.106744","journal-title":"Knowl. Based Syst."}],"container-title":["International Journal on Digital Libraries"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00799-022-00339-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00799-022-00339-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00799-022-00339-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T20:09:07Z","timestamp":1668110947000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00799-022-00339-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,5]]},"references-count":124,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["339"],"URL":"https:\/\/doi.org\/10.1007\/s00799-022-00339-w","relation":{},"ISSN":["1432-5012","1432-1300"],"issn-type":[{"value":"1432-5012","type":"print"},{"value":"1432-1300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,5]]},"assertion":[{"value":"23 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 October 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}