{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T12:10:09Z","timestamp":1743077409640,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030602581"},{"type":"electronic","value":"9783030602598"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60259-8_41","type":"book-chapter","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T10:04:33Z","timestamp":1602756273000},"page":"558-573","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Author Contributed Representation for Scholarly Network"],"prefix":"10.1007","author":[{"given":"Binglei","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanmin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Le","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lintao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guiquan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enhong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,16]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed, A., Shervashidze, N., Narayanamurthy, S., Josifovski, V., Smola, A.J.: Distributed large-scale natural graph factorization. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 37\u201348. ACM (2013)","DOI":"10.1145\/2488388.2488393"},{"key":"41_CR2","unstructured":"Ammar, W., et al.: Construction of the literature graph in semantic scholar. arXiv preprint arXiv:1805.02262 (2018)"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Belkin, M., Niyogi, P.: Laplacian eigenmaps and spectral techniques for embedding and clustering. In: Advances in Neural Information Processing Systems, pp. 585\u2013591 (2002)","DOI":"10.7551\/mitpress\/1120.003.0080"},{"key":"41_CR4","unstructured":"Dong, Y., Johnson, R.A., Chawla, N.V.: Will this paper increase your h-index? Scientific impact prediction. In: Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, pp. 149\u2013158 (2015)"},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Du, D., et al.: Solving link-oriented tasks in signed network via an embedding approach. In: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 75\u201380. IEEE (2017)","DOI":"10.1109\/SMC.2017.8122581"},{"key":"41_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/978-3-319-56608-5_30","volume-title":"Advances in Information Retrieval","author":"S Ganguly","year":"2017","unstructured":"Ganguly, S., Pudi, V.: Paper2vec: combining graph and text information for scientific paper representation. In: Jose, J.M., Hauff, C., Alt\u0131ngovde, I.S., Song, D., Albakour, D., Watt, S., Tait, J. (eds.) ECIR 2017. LNCS, vol. 10193, pp. 383\u2013395. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-56608-5_30"},{"key":"41_CR7","doi-asserted-by":"crossref","unstructured":"Grover, A., Leskovec, J.: node2vec: scalable feature learning for networks. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 855\u2013864. ACM (2016)","DOI":"10.1145\/2939672.2939754"},{"key":"41_CR8","unstructured":"Hamilton, W., Ying, Z., Leskovec, J.: Inductive representation learning on large graphs. In: Advances in Neural Information Processing Systems, pp. 1024\u20131034 (2017)"},{"key":"41_CR9","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"41_CR10","unstructured":"Lawrence, N.D., Bishop, C.M., Jordan, M.I.: Mixture representations for inference and learning in Boltzmann machines. arXiv preprint arXiv:1301.7393 (2013)"},{"key":"41_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1007\/978-3-319-91458-9_29","volume-title":"Database Systems for Advanced Applications","author":"H Lin","year":"2018","unstructured":"Lin, H., Wang, H., Du, D., Wu, H., Chang, B., Chen, E.: Patent quality valuation with deep learning models. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds.) DASFAA 2018. LNCS, vol. 10828, pp. 474\u2013490. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-91458-9_29"},{"issue":"50","key":"41_CR12","doi-asserted-by":"publisher","first-page":"12608","DOI":"10.1073\/pnas.1800485115","volume":"115","author":"Y Ma","year":"2018","unstructured":"Ma, Y., Uzzi, B.: Scientific prize network predicts who pushes the boundaries of science. Proc. Natl. Acad. Sci. 115(50), 12608\u201312615 (2018)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"41_CR13","unstructured":"Murphy, K., Weiss, Y., Jordan, M.I.: Loopy belief propagation for approximate inference: an empirical study. arXiv preprint arXiv:1301.6725 (2013)"},{"issue":"9","key":"41_CR14","first-page":"12","volume":"11","author":"S Pan","year":"2016","unstructured":"Pan, S., Wu, J., Zhu, X., Zhang, C., Wang, Y.: Tri-party deep network representation. Network 11(9), 12 (2016)","journal-title":"Network"},{"key":"41_CR15","unstructured":"Pei, H., Wei, B., Chang, K.C.C., Lei, Y., Yang, B.: Geom-GCN: geometric graph convolutional networks. In: International Conference on Learning Representations (ICLR) (2020)"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Perozzi, B., Al-Rfou, R., Skiena, S.: DeepWalk: online learning of social representations. In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 701\u2013710. ACM (2014)","DOI":"10.1145\/2623330.2623732"},{"issue":"34","key":"41_CR17","doi-asserted-by":"publisher","first-page":"E4671","DOI":"10.1073\/pnas.1501444112","volume":"112","author":"AM Petersen","year":"2015","unstructured":"Petersen, A.M.: Quantifying the impact of weak, strong, and super ties in scientific careers. Proc. Natl. Acad. Sci. 112(34), E4671\u2013E4680 (2015)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"41_CR18","doi-asserted-by":"crossref","unstructured":"Sinha, A., et al.: An overview of Microsoft Academic Service (MAS) and applications. In: Proceedings of the 24th International Conference on World Wide Web, pp. 243\u2013246. ACM (2015)","DOI":"10.1145\/2740908.2742839"},{"key":"41_CR19","doi-asserted-by":"crossref","unstructured":"Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., Mei, Q.: Line: large-scale information network embedding. In: Proceedings of the 24th International Conference on World Wide Web, pp. 1067\u20131077. International World Wide Web Conferences Steering Committee (2015)","DOI":"10.1145\/2736277.2741093"},{"key":"41_CR20","doi-asserted-by":"crossref","unstructured":"Tao, S., Wang, X., Huang, W., Chen, W., Wang, T., Lei, K.: From citation network to study map: a novel model to reorganize academic literatures. In: Proceedings of the 26th International Conference on World Wide Web Companion, pp. 1225\u20131232 (2017)","DOI":"10.1145\/3041021.3053059"},{"key":"41_CR21","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"41_CR22","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: A united approach to learning sparse attributed network embedding. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 557\u2013566. IEEE (2018)","DOI":"10.1109\/ICDM.2018.00071"},{"key":"41_CR23","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: MCNE: an end-to-end framework for learning multiple conditional network representations of social network. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1064\u20131072 (2019)","DOI":"10.1145\/3292500.3330931"},{"issue":"2","key":"41_CR24","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1109\/TBDATA.2016.2541167","volume":"2","author":"JD West","year":"2016","unstructured":"West, J.D., Wesley-Smith, I., Bergstrom, C.T.: A recommendation system based on hierarchical clustering of an article-level citation network. IEEE Trans. Big Data 2(2), 113\u2013123 (2016)","journal-title":"IEEE Trans. Big Data"},{"issue":"1","key":"41_CR25","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/TBDATA.2016.2641460","volume":"3","author":"F Xia","year":"2017","unstructured":"Xia, F., Wang, W., Bekele, T.M., Liu, H.: Big scholarly data: a survey. IEEE Trans. Big Data 3(1), 18\u201335 (2017)","journal-title":"IEEE Trans. Big Data"},{"key":"41_CR26","doi-asserted-by":"publisher","first-page":"1643","DOI":"10.1007\/978-1-4614-6170-8_249","volume-title":"Encyclopedia of Social Network Analysis and Mining","author":"E Yan","year":"2014","unstructured":"Yan, E., Ding, Y.: Scholarly networks analysis. In: Alhajj, R., Rokne, J. (eds.) Encyclopedia of Social Network Analysis and Mining, pp. 1643\u20131651. Springer, New York (2014). https:\/\/doi.org\/10.1007\/978-1-4614-6170-8_249"},{"key":"41_CR27","unstructured":"Yang, C., Liu, Z., Zhao, D., Sun, M., Chang, E.: Network representation learning with rich text information. In: Twenty-Fourth International Joint Conference on Artificial Intelligence (2015)"},{"key":"41_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, D., Yin, J., Zhu, X., Zhang, C.: User profile preserving social network embedding. In: IJCAI International Joint Conference on Artificial Intelligence (2017)","DOI":"10.24963\/ijcai.2017\/472"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60259-8_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T23:13:24Z","timestamp":1723763604000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60259-8_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030602581","9783030602598"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60259-8_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"16 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.tjudb.cn\/apwebwaim2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"259","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"68","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"37","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4.6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was organized as a fully online conference.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}