{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T23:01:21Z","timestamp":1781218881756,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":10,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811674754","type":"print"},{"value":"9789811674761","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-7476-1_6","type":"book-chapter","created":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T11:09:50Z","timestamp":1635592190000},"page":"59-72","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Network Based Quantitative Method for the Mining and Visualization of Music Influence"],"prefix":"10.1007","author":[{"given":"Jiachen","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinning","family":"Chi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyang","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,10,31]]},"reference":[{"key":"6_CR1","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1057\/s41599-019-0221-1","volume":"5","author":"PE Savage","year":"2019","unstructured":"Savage, P.E.: Cultural evolution of music. Palgrave Commun. 5, 16 (2019)","journal-title":"Palgrave Commun."},{"issue":"1","key":"6_CR2","first-page":"105","volume":"9","author":"J-J Aucouturier","year":"2003","unstructured":"Aucouturier, J.-J., Pachet, F.: Music similarity measures: what\u2019s the use? Ismir 9(1), 105\u2013106 (2003)","journal-title":"Ismir"},{"issue":"1","key":"6_CR3","first-page":"32","volume":"14","author":"K Gurjar","year":"2018","unstructured":"Gurjar, K., Moon, Y.-S.: A comparative analysis of music similarity measures in music information retrieval systems. J. Inf. Process. Syst. 14(1), 32\u201355 (2018)","journal-title":"J. Inf. Process. Syst."},{"issue":"12","key":"6_CR4","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1049\/el.2019.4202","volume":"56","author":"A Elbir","year":"2020","unstructured":"Elbir, A., Aydin, N.: Music genre classification and music recommendation by using deep learning. Electron. Lett. 56(12), 627\u2013629 (2020)","journal-title":"Electron. Lett."},{"key":"6_CR5","unstructured":"Tang, C.P., Chui, K.L., Yu, Y.K., Zeng, Z., Wong, K.H.: Mu-sic genre classification using a hierarchical long-short term memory (LSTM) model. In: Proceedings SPIE 10828, Third International Workshop on Pattern Recognition, p. 108281B (2018)"},{"issue":"5","key":"6_CR6","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1109\/TSA.2002.800560","volume":"10","author":"G Tzanetakis","year":"2002","unstructured":"Tzanetakis, G., Cook, P.: Musical genre classification of audio signals. IEEE Trans. Speech Audio Process. 10(5), 293\u2013302 (2002)","journal-title":"IEEE Trans. Speech Audio Process."},{"key":"6_CR7","unstructured":"Mandel, M., Ellis, D.: Song-level features and support vector machines for music classification. In: Proceedings 6th International Conference Music Information Retrieval, pp. 594\u2013599 (2005)"},{"key":"6_CR8","unstructured":"Wyse, L.: Audio spectrogram representations for processing with convolutional neural networks. In: Proceedings of the First International Conference on Deep Learning and Music, Anchorage, US, May, 2017, pp. 37\u201341 (2017)."},{"issue":"1","key":"6_CR9","first-page":"11","volume":"2180","author":"TL Li","year":"2010","unstructured":"Li, T.L., Chan, A.B., Chun, A.H.: Automatic musical pattern feature extraction using convolutional neural network. Lect. Notes Eng. Comput. Sci. 2180(1), 11 (2010)","journal-title":"Lect. Notes Eng. Comput. Sci."},{"key":"6_CR10","unstructured":"Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Stanford InfoLab, pp. 1\u201314 (1998)"}],"container-title":["Communications in Computer and Information Science","Data Mining and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-7476-1_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T22:02:45Z","timestamp":1758578565000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-7476-1_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811674754","9789811674761"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-7476-1_6","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"31 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DMBD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Data Mining and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","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":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dmbd2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/nsclab.org\/dmbd2021\/index.html","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":"258","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":"57","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":"28","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":"22% - 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":"2.5","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":"8","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)"}}]}}