{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:37:09Z","timestamp":1743043029047,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031496103"},{"type":"electronic","value":"9783031496110"}],"license":[{"start":{"date-parts":[[2023,12,9]],"date-time":"2023-12-09T00:00:00Z","timestamp":1702080000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,9]],"date-time":"2023-12-09T00:00:00Z","timestamp":1702080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-49611-0_8","type":"book-chapter","created":{"date-parts":[[2023,12,8]],"date-time":"2023-12-08T14:02:45Z","timestamp":1702044165000},"page":"107-125","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Minimum Monotone Tree Decomposition of\u00a0Density Functions Defined on\u00a0Graphs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9844-7497","authenticated-orcid":false,"given":"Lucas","family":"Magee","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7950-4348","authenticated-orcid":false,"given":"Yusu","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,9]]},"reference":[{"key":"8_CR1","doi-asserted-by":"crossref","unstructured":"Aanjaneya, M., Chazal, F., Chen, D., Glisse, M., Guibas, L., Morozov, D.: Metric graph reconstruction from noisy data. In: Proceedings of 27th Symposium on Computational Geometry, pp. 37\u201346 (2011)","DOI":"10.1145\/1998196.1998203"},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1038\/s42256-020-0227-9","volume":"2","author":"S Banerjee","year":"2020","unstructured":"Banerjee, S., et al.: Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder-decoder deep networks. Nat. Mach. Intell. 2, 585\u2013594 (2020)","journal-title":"Nat. Mach. Intell."},{"key":"8_CR3","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/s41468-019-00046-7","volume":"4","author":"Y Baryshnikov","year":"2020","unstructured":"Baryshnikov, Y., Ghrist, R.: Minimal unimodal decompositions on trees. J. Appl. Comput. Topol. 4, 199\u2013209 (2020)","journal-title":"J. Appl. Comput. Topol."},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Chazal, F., Huang, R., Sun, J.: Gromov-Hausdorff approximation of filamentary structures using reeb-type graphs. Discrete Comput. Geom. 53(3), 621\u2013649 (2015)","DOI":"10.1007\/s00454-015-9674-1"},{"issue":"3","key":"8_CR5","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s40708-015-0018-y","volume":"2","author":"H Chen","year":"2015","unstructured":"Chen, H., Xiao, H., Liu, T., Peng, H.: SmartTracing: self-learning-based neuron reconstruction. Brain Inform. 2(3), 135\u2013144 (2015)","journal-title":"Brain Inform."},{"key":"8_CR6","unstructured":"Dey, T.K., Wang, J., Wang, Y.: Graph reconstruction by discrete Morse theory. In: Proceedings of International Symposoium on Computational Geometry, pp. 31:1\u201331:15 (2018)"},{"key":"8_CR7","unstructured":"Garey, M.R., Johnson, D.S.: Computers and Intractability, vol. 174. Freeman, San Francisco (1979)"},{"key":"8_CR8","unstructured":"Ge, X., Safa, I.I., Belkin, M., Wang, Y.: Data skeletonization via reeb graphs. In: Shawe-Taylor, J., Zemel, R.S., Bartlett, P.L., Pereira, F., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 24, pp. 837\u2013845. Curran Associates, Inc. (2011)"},{"key":"8_CR9","doi-asserted-by":"crossref","unstructured":"Hang, Z., et al.: Dense reconstruction of brain-wide neuronal population close to the ground truth. bioRxiv (2018)","DOI":"10.1101\/223834"},{"issue":"4","key":"8_CR10","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1073\/pnas.39.4.315","volume":"39","author":"F Harary","year":"1953","unstructured":"Harary, F., Uhlenbeck, G.E.: On the number of Husimi trees: I. Proc. Natl. Acad. Sci. 39(4), 315\u2013322 (1953)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Hare, E., Hedetniemi, S., Laskar, R., Peters, K., Wimer, T.: Linear-time computability of combinatorial problems on generalized-series-parallel graphs. In: Johnson, D.S., Nishizeki, T., Nozaki, A., Wilf, H.S. (eds.) Discrete Algorithms and Complexity, pp. 437\u2013457. Academic Press (1987)","DOI":"10.1016\/B978-0-12-386870-1.50030-7"},{"key":"8_CR12","doi-asserted-by":"crossref","unstructured":"Hastie, T.J.: Principal curves and surfaces. Ph.D. thesis, Stanford University (1984)","DOI":"10.21236\/ADA148833"},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"K\u00e9gl, B., Krzy\u017cak, A.: Piecewise linear skeletonization using principal curves. IEEE Trans. Pattern Anal. Machine Intell. 24, 59\u201374 (2002)","DOI":"10.1109\/34.982884"},{"key":"8_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1007\/3-540-45022-X_53","volume-title":"Automata, Languages and Programming","author":"VSA Kumar","year":"2000","unstructured":"Kumar, V.S.A., Arya, S., Ramesh, H.: Hardness of set cover with intersection 1. In: Montanari, U., Rolim, J.D.P., Welzl, E. (eds.) ICALP 2000. LNCS, vol. 1853, pp. 624\u2013635. Springer, Heidelberg (2000). https:\/\/doi.org\/10.1007\/3-540-45022-X_53"},{"key":"8_CR15","unstructured":"Lecci, F., Rinaldo, A., Wasserman, L.: Statistical analysis of metric graph reconstruction. J. Mach. Learn. Res. 15(1), 3425\u20133446 (2014)"},{"key":"8_CR16","first-page":"429","volume":"13","author":"L Magee","year":"2022","unstructured":"Magee, L., Wang, Y.: Graph skeletonization of high-dimensional point cloud data via topological method. J. Comput. Geometry 13, 429\u2013470 (2022)","journal-title":"J. Comput. Geometry"},{"issue":"5","key":"8_CR17","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/0167-6377(82)90039-6","volume":"1","author":"N Megiddo","year":"1982","unstructured":"Megiddo, N., Tamir, A.: On the complexity of locating linear facilities in the plane. Oper. Res. Lett. 1(5), 194\u2013197 (1982)","journal-title":"Oper. Res. Lett."},{"key":"8_CR18","first-page":"1249","volume":"12","author":"U Ozertem","year":"2011","unstructured":"Ozertem, U., Erdogmus, D.: Locally defined principal curves and surfaces. J. Mach. Learn. Res. 12, 1249\u20131286 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"8_CR19","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1038\/nmeth.3662","volume":"13","author":"T Quan","year":"2016","unstructured":"Quan, T., et al.: Neurogps-tree: automatic reconstruction of large-scale neuronal populations with dense neurites. Nat. Methods 13(1), 51\u201354 (2016)","journal-title":"Nat. Methods"},{"key":"8_CR20","doi-asserted-by":"crossref","unstructured":"Sousbie, T.: The persistent cosmic web and its filamentary structure i. Theory and implementation. Mon. Not. Roy. Astron. Soc. 414, 350\u2013383 (2011)","DOI":"10.1111\/j.1365-2966.2011.18394.x"},{"key":"8_CR21","doi-asserted-by":"crossref","unstructured":"Wang, D., et al.: Detection and skeletonization of single neurons and tracer injections using topological methods. arXiv preprint arXiv:2004.02755 (2020)","DOI":"10.1101\/2020.03.21.000323"},{"key":"8_CR22","doi-asserted-by":"crossref","unstructured":"Wang, S., Wang, Y., Li, Y.: Efficient map reconstruction and augmentation via topological methods. In: Proceedings of 23rd ACM SIGSPATIAL, p. 25. ACM (2015)","DOI":"10.1145\/2820783.2820833"}],"container-title":["Lecture Notes in Computer Science","Combinatorial Optimization and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-49611-0_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,10]],"date-time":"2024-02-10T09:07:15Z","timestamp":1707556035000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-49611-0_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,9]]},"ISBN":["9783031496103","9783031496110"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-49611-0_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,9]]},"assertion":[{"value":"9 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"COCOA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Combinatorial Optimization and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hawai, HI","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cocoa2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/theory.utdallas.edu\/COCOA2023\/","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":"EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"117","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":"73","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":"0","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":"62% - 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":"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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}