{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T22:42:17Z","timestamp":1774219337017,"version":"3.50.1"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030346362","type":"print"},{"value":"9783030346379","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","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":[[2019]]},"DOI":"10.1007\/978-3-030-34637-9_8","type":"book-chapter","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T00:04:15Z","timestamp":1575590655000},"page":"106-118","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Application of DeepWalk Based on Hyperbolic Coordinates on Unsupervised Clustering"],"prefix":"10.1007","author":[{"given":"Shikang","family":"Yu","sequence":"first","affiliation":[]},{"given":"Yang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Yurong","family":"Song","sequence":"additional","affiliation":[]},{"given":"Guoping","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Xiaoping","family":"Su","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,6]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1007\/978-1-4419-1153-7_200110","volume-title":"Encyclopedia of Machine Learning","author":"E Keogh","year":"2011","unstructured":"Keogh, E., Mueen, A.: Curse of dimensionality. In: Gass, S.I., Fu, M.C. (eds.) Encyclopedia of Machine Learning, pp. 257\u2013258. Springer, Boston (2011). \nhttps:\/\/doi.org\/10.1007\/978-1-4419-1153-7_200110"},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"2","key":"8_CR3","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MCI.2014.2307227","volume":"9","author":"E Cambria","year":"2014","unstructured":"Cambria, E., White, B.: Jumping NLP curves: a review of natural language processing research. IEEE Comput. Intell. Mag. 9(2), 48\u201357 (2014)","journal-title":"IEEE Comput. Intell. Mag."},{"key":"8_CR4","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.1109\/TKDE.2018.2807452","volume":"30","author":"H Cai","year":"2018","unstructured":"Cai, H., Zheng, V.W., Chang, K.: A comprehensive survey of graph embedding: problems, techniques and applications. IEEE Trans. Knowl. Data Eng. 30, 1616\u20131637 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"8_CR5","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.knosys.2018.03.022","volume":"151","author":"P Goyal","year":"2018","unstructured":"Goyal, P., Ferrara, E.: Graph embedding techniques, applications, and performance: a survey. Knowl. Based Syst. 151, 78\u201394 (2018)","journal-title":"Knowl. Based Syst."},{"key":"8_CR6","doi-asserted-by":"crossref","unstructured":"Grbovic, M., et al.: E-commerce in your inbox: product recommendations at scale. In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1809\u20131818. ACM, August 2015","DOI":"10.1145\/2783258.2788627"},{"key":"8_CR7","doi-asserted-by":"crossref","unstructured":"Barkan, O., Koenigstein, N.: Item2Vec: neural item embedding for collaborative filtering. In: 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1\u20136. IEEE, September 2016","DOI":"10.1109\/MLSP.2016.7738886"},{"key":"8_CR8","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, August 2016","DOI":"10.1145\/2939672.2939754"},{"issue":"3","key":"8_CR9","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1109\/TSIPN.2017.2731163","volume":"3","author":"W Ding","year":"2017","unstructured":"Ding, W., Lin, C., Ishwar, P.: Node embedding via word embedding for network community discovery. IEEE Trans. Signal Inf. Process. Netw. 3(3), 539\u2013552 (2017)","journal-title":"IEEE Trans. Signal Inf. Process. Netw."},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Kooti, F., Grbovic, M., Aiello, L.M., Bax, E., Lerman, K.: iPhone\u2019s digital marketplace: characterizing the big spenders. In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, pp. 13\u201321. ACM, February 2017","DOI":"10.1145\/3018661.3018697"},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Chamberlain, B.P., Cardoso, A., Liu, C.H., Pagliari, R., Deisenroth, M.P.: Customer lifetime value prediction using embeddings. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1753\u20131762. ACM, August 2017","DOI":"10.1145\/3097983.3098123"},{"key":"8_CR12","unstructured":"Perozzi, B., Kulkarni, V., Skiena, S.: Walklets: multiscale graph embeddings for interpretable network classification. arXiv preprint \narXiv:1605.02115\n\n (2016)"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Li, J., Zhu, J., Zhang, B.: Discriminative deep random walk for network classification. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol. 1, pp. 1004\u20131013 (2016)","DOI":"10.18653\/v1\/P16-1095"},{"key":"8_CR14","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, August 2014","DOI":"10.1145\/2623330.2623732"},{"issue":"4","key":"8_CR15","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1075\/ijcl.11.4.04che","volume":"11","author":"W Cheng","year":"2006","unstructured":"Cheng, W., Greaves, C., Warren, M.: From n-gram to SkipGram to concgram. Int. J. Corpus Linguist. 11(4), 411\u2013433 (2006)","journal-title":"Int. J. Corpus Linguist."},{"key":"8_CR16","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, May 2015","DOI":"10.1145\/2736277.2741093"},{"key":"8_CR17","unstructured":"Chamberlain, B.P., Clough, J., Deisenroth, M.P.: Neural embeddings of graphs in hyperbolic space. arXiv preprint \narXiv:1705.10359\n\n (2017)"},{"issue":"3","key":"8_CR18","doi-asserted-by":"publisher","first-page":"036106","DOI":"10.1103\/PhysRevE.82.036106","volume":"82","author":"D Krioukov","year":"2010","unstructured":"Krioukov, D., Papadopoulos, F., Kitsak, M., Vahdat, A., Bogun\u00e1, M.: Hyperbolic geometry of complex networks. Phys. Rev. E 82(3), 036106 (2010)","journal-title":"Phys. Rev. E"},{"issue":"7417","key":"8_CR19","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1038\/nature11459","volume":"489","author":"F Papadopoulos","year":"2012","unstructured":"Papadopoulos, F., Kitsak, M., Serrano, M.\u00c1., Bogun\u00e1, M., Krioukov, D.: Popularity versus similarity in growing networks. Nature 489(7417), 537 (2012)","journal-title":"Nature"},{"issue":"1","key":"8_CR20","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1109\/TNET.2013.2294052","volume":"23","author":"F Papadopoulos","year":"2015","unstructured":"Papadopoulos, F., Psomas, C., Krioukov, D.: Network mapping by replaying hyperbolic growth. IEEE\/ACM Trans. Netw. (TON) 23(1), 198\u2013211 (2015)","journal-title":"IEEE\/ACM Trans. Netw. (TON)"},{"key":"8_CR21","unstructured":"Lov\u00e1sz, L.: Random walks on graphs: a survey. In: Combinatorics, Paul Erdos Is Eighty, vol. 2(1), pp. 1\u201346 (1993)"},{"issue":"4","key":"8_CR22","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1112\/blms\/27.4.353","volume":"27","author":"DM Duc","year":"1995","unstructured":"Duc, D.M., van Hieu, N.: Graphs with prescribed mean curvature on Poincar\u00e9 disk. Bull. Lond. Math. Soc. 27(4), 353\u2013358 (1995)","journal-title":"Bull. Lond. Math. Soc."},{"issue":"3","key":"8_CR23","doi-asserted-by":"publisher","first-page":"036104","DOI":"10.1103\/PhysRevE.74.036104","volume":"74","author":"ME Newman","year":"2006","unstructured":"Newman, M.E.: Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E 74(3), 036104 (2006)","journal-title":"Phys. Rev. E"},{"key":"8_CR24","unstructured":"Scikit-learn developers. Custering. \nhttps:\/\/scikit-learn.org\/stable\/modules\/clustering.html#clustering-performance-evaluation\n\n. Accessed 24 Feb 2019"}],"container-title":["Lecture Notes in Computer Science","Science of Cyber Security"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-34637-9_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T00:05:14Z","timestamp":1575590714000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-34637-9_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030346362","9783030346379"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-34637-9_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"6 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SciSec","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Science of Cyber Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"scisec2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.sci-cs.net\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"62","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":"20","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":"8","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":"32% - 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":"3","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}