{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T04:52:59Z","timestamp":1743051179035,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":62,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819703159"},{"type":"electronic","value":"9789819703166"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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\/978-981-97-0316-6_2","type":"book-chapter","created":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T19:02:19Z","timestamp":1707850939000},"page":"18-37","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generating High Dimensional Test Data for\u00a0Topological Data Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2872-1232","authenticated-orcid":false,"given":"Rohit P.","family":"Singh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3848-4381","authenticated-orcid":false,"given":"Nicholas O.","family":"Malott","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Blake","family":"Sauerwein","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil","family":"Mcgrogan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6562-8646","authenticated-orcid":false,"given":"Philip A.","family":"Wilsey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,14]]},"reference":[{"key":"2_CR1","unstructured":"Abbott, J., Bigatti, A.M.: CoCoA and CoCoALib: fast prototyping and flexible C++ library for computations in commutative algebra. In: \u00c1brah\u00e1m, E., Davenport, J.H., Fontaine, P. (eds.) Proceedings of the 1st Workshop on Satisfiability Checking and Symbolic Computation co-located with 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. CEUR Workshop Proceedings, vol. 1804, pp. 1\u20133. CEUR-WS.org (2016)"},{"key":"2_CR2","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/s41468-021-00071-5","volume":"5","author":"U Bauer","year":"2021","unstructured":"Bauer, U.: Ripser: efficient computation of vietoris-rips persistence barcodes. J. Appl. Comput. Topol. 5, 391\u2013423 (2021). https:\/\/doi.org\/10.1007\/s41468-021-00071-5","journal-title":"J. Appl. Comput. Topol."},{"key":"2_CR3","series-title":"Mathematics and Visualization","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/978-3-319-04099-8_7","volume-title":"Topological Methods in Data Analysis and Visualization III","author":"U Bauer","year":"2014","unstructured":"Bauer, U., Kerber, M., Reininghaus, J.: Clear and compress: computing persistent homology in chunks. In: Bremer, P.-T., Hotz, I., Pascucci, V., Peikert, R. (eds.) Topological Methods in Data Analysis and Visualization III. MV, pp. 103\u2013117. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-04099-8_7"},{"issue":"6","key":"2_CR4","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1109\/TVCG.2010.139","volume":"16","author":"P Bendich","year":"2010","unstructured":"Bendich, P., Edelsbrunner, H., Kerber, M.: Computing robustness and persistence for images. IEEE Trans. Visual Comput. Graphics 16(6), 1251\u20131260 (2010). https:\/\/doi.org\/10.1109\/TVCG.2010.139","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"issue":"4A","key":"2_CR5","doi-asserted-by":"publisher","first-page":"2257","DOI":"10.3150\/16-BEJ810","volume":"23","author":"M Betancourt","year":"2017","unstructured":"Betancourt, M., Byrne, S., Livingstone, S., Girolami, M.: The geometric foundations of Hamiltonian Monte Carlo. Bernoulli 23(4A), 2257\u20132298 (2017). https:\/\/doi.org\/10.3150\/16-BEJ810","journal-title":"Bernoulli"},{"key":"2_CR6","doi-asserted-by":"publisher","unstructured":"Bingham, E., Mannila, H.: Random projection in dimensionality reduction: applications to image and text data. In: Knowledge Discovery and Data Mining, KDD 2001, pp. 245\u2013250. ACM Press (2001). https:\/\/doi.org\/10.1145\/502512.502546","DOI":"10.1145\/502512.502546"},{"key":"2_CR7","unstructured":"Bloomenthal, J., Wyvill, B. (eds.): Introduction to Implicit Surfaces. Morgan Kaufmann (Jul 1997)"},{"key":"2_CR8","unstructured":"Board, G.E.: GUDHI datasets manual. https:\/\/gudhi.inria.fr\/python\/latest\/datasets.html"},{"key":"2_CR9","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/s41468-017-0010-0","volume":"1","author":"O Bobrowski","year":"2018","unstructured":"Bobrowski, O., Kahle, M.: Topology of random geometric complexes: a survey. J. Appl. Comput. Topol. 1, 331\u2013364 (2018). https:\/\/doi.org\/10.1007\/s41468-017-0010-0","journal-title":"J. Appl. Comput. Topol."},{"issue":"4","key":"2_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3229146","volume":"14","author":"JD Boissonnat","year":"2018","unstructured":"Boissonnat, J.D., Karthik, C.S.: An efficient representation for filtrations of simplicial complexes. ACM Trans. Algorithms 14(4), 1\u201321 (2018). https:\/\/doi.org\/10.1145\/3229146","journal-title":"ACM Trans. Algorithms"},{"key":"2_CR11","doi-asserted-by":"publisher","unstructured":"Boissonnat, J.D., Pritam, S., Pareek, D.: Strong collapse for persistence. In: Azar, Y., Bast, H., Herman, G. (eds.) 26th Annual European Symposium on Algorithms (ESA 2018). Leibniz International Proceedings in Informatics (LIPIcs), vol. 112, pp. 67:1\u201367:13. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl (2018). https:\/\/doi.org\/10.4230\/LIPIcs.ESA.2018.67","DOI":"10.4230\/LIPIcs.ESA.2018.67"},{"issue":"4","key":"2_CR12","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1093\/bioinformatics\/btw705","volume":"33","author":"S Cacciatore","year":"2016","unstructured":"Cacciatore, S., Tenori, L., Luchinat, C., Bennett, P.R., MacIntyre, D.A.: Kodama: an R package for knowledge discovery and data mining. Bioinformatics 33(4), 621\u2013623 (2016). https:\/\/doi.org\/10.1093\/bioinformatics\/btw705","journal-title":"Bioinformatics"},{"issue":"1","key":"2_CR13","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.cels.2016.05.008","volume":"3","author":"PG Camara","year":"2016","unstructured":"Camara, P.G., Rosenbloom, D.I.S., Emmett, K.J., Levine, A.J., Rabadan, R.: Topological data analysis generates high-resolution, genome-wide maps of human recombination. Cell Syst. 3(1), 83\u201394 (2016). https:\/\/doi.org\/10.1016\/j.cels.2016.05.008","journal-title":"Cell Syst."},{"issue":"1","key":"2_CR14","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1515\/mlbmb-2015-0009","volume":"3","author":"Z Cang","year":"2015","unstructured":"Cang, Z., Mu, L., Wu, K., Opron, K., Xia, K., Wei, G.W.: A topological approach for protein classification. Mol. Based Math. Biol. 3(1), 140\u2013162 (2015). https:\/\/doi.org\/10.1515\/mlbmb-2015-0009","journal-title":"Mol. Based Math. Biol."},{"key":"2_CR15","unstructured":"Cappell, S., Ranicki, A., Rosenberg, J. (eds.): Surveys on Surgery Theory: Papers Dedicated to C.T.C. Wall (AM-145). Annals of Mathematics Studies, vol. 1. Princeton University Press (2000)"},{"issue":"2","key":"2_CR16","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1090\/S0273-0979-09-01249-X","volume":"46","author":"G Carlsson","year":"2009","unstructured":"Carlsson, G.: Topology and data. Bull. Am. Math. Soc. 46(2), 255\u2013308 (2009). https:\/\/doi.org\/10.1090\/S0273-0979-09-01249-X","journal-title":"Bull. Am. Math. Soc."},{"issue":"1","key":"2_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-007-0056-x","volume":"76","author":"G Carlsson","year":"2008","unstructured":"Carlsson, G., Ishkhanov, T., de Silva, V., Zomorodian, A.: On the local behavior of spaces of natural images. Int. J. Comput. Vision 76(1), 1\u201312 (2008). https:\/\/doi.org\/10.1007\/s11263-007-0056-x","journal-title":"Int. J. Comput. Vision"},{"key":"2_CR18","unstructured":"Chakour, E.: An exploration of higher dimensional objects (2018)"},{"issue":"46","key":"2_CR19","doi-asserted-by":"publisher","first-page":"18566","DOI":"10.1073\/pnas.1313480110","volume":"110","author":"JM Chan","year":"2013","unstructured":"Chan, J.M., Carlsson, G., Rabadan, R.: Topology of viral evolution. Proc. Natl. Acad. Sci. 110(46), 18566\u201318571 (2013). https:\/\/doi.org\/10.1073\/pnas.1313480110","journal-title":"Proc. Natl. Acad. Sci."},{"key":"2_CR20","unstructured":"Chazal, F., Fasy, B.T., Lecci, F., Michel, B., Rinaldo, A., Wasserman, L.: Subsampling methods for persistent homology. In: International Conference on Machine Learning, ICML 2015, Lille, France, vol. 37, pp. 2143\u20132151 (2015)"},{"key":"2_CR21","doi-asserted-by":"publisher","unstructured":"Chazal, F., Michel, B.: An introduction to topological data analysis: fundamental and practical aspects for data scientists. Front. Artif. Intell. 4 (2021). https:\/\/doi.org\/10.3389\/frai.2021.667963","DOI":"10.3389\/frai.2021.667963"},{"key":"2_CR22","unstructured":"Chen, C., Kerber, M.: Persistent homology computation with a twist. In: Proceedings 27th European Workshop on Computational Geometry (EuroCG 2011), pp. 197\u2013200 (2011)"},{"key":"2_CR23","unstructured":"Ciarelli, P.M., Oliveira, E.: UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml\/datasets\/CNAE-9"},{"key":"2_CR24","doi-asserted-by":"publisher","unstructured":"de Silva, V., Carlsson, G.: Topological estimation using witness complexes. In: Gross, M., Pfister, H., Alexa, M., Rusinkiewicz, S. (eds.) Eurographics Symposium on Point-Based Graphics, pp. 157\u2013166. SPBG 2004. The Eurographics Association, Goslar, DEU (2004). https:\/\/doi.org\/10.2312\/SPBG\/SPBG04\/157-166","DOI":"10.2312\/SPBG\/SPBG04\/157-166"},{"key":"2_CR25","unstructured":"Decker, W., Greuel, G.M., Pfister, G., Schonemann, H.: Singular 4.3.0 \u2013 a computer algebra system for polynomial computations (2022). http:\/\/www.singular.uni-kl.de"},{"key":"2_CR26","doi-asserted-by":"publisher","unstructured":"Dey, T.K., Mandal, S.: Protein classification with improved topological data analysis. In: 18th International Workshop on Algorithms in Bioinformatics, WABI 2018, vol. 113, pp. 6:1\u20136:13. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl (2019). https:\/\/doi.org\/10.4230\/LIPIcs.WABI.2018.6","DOI":"10.4230\/LIPIcs.WABI.2018.6"},{"key":"2_CR27","doi-asserted-by":"publisher","unstructured":"Dey, T.K., Shi, D., Wang, Y.: SimBa: an efficient tool for approximating rips-filtration persistence via simplicial batch-collapse. In: Sankowski, P., Zaroliagis, C. (eds.) 24th Annual European Symposium on Algorithms (ESA 2016). Leibniz International Proceedings in Informatics (LIPIcs), vol. 57, pp. 35:1\u201335:16. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl (2016). https:\/\/doi.org\/10.4230\/LIPIcs.ESA.2016.206","DOI":"10.4230\/LIPIcs.ESA.2016.206"},{"issue":"1","key":"2_CR28","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1007\/s00454-012-9463-z","volume":"49","author":"TK Dey","year":"2013","unstructured":"Dey, T.K., Wang, Y.: Reeb graphs: approximation and persistence. Discrete Comput. Geom. 49(1), 46\u201373 (2013). https:\/\/doi.org\/10.1007\/s00454-012-9463-z","journal-title":"Discrete Comput. Geom."},{"key":"2_CR29","doi-asserted-by":"publisher","unstructured":"Diaconis, P., Holmes, S., Shahshahani, M.: Sampling from a manifold. In: Advances in Modern Statistical Theory and Applications: A Festschrift in honor of Morris L. Eaton, vol. 10, pp. 102\u2013125 (2013). https:\/\/doi.org\/10.1214\/12-IMSCOLL1006. (also published in arXiv Statistics Theory)","DOI":"10.1214\/12-IMSCOLL1006"},{"key":"2_CR30","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1090\/conm\/453\/08802","volume":"453","author":"H Edelsbrunner","year":"2008","unstructured":"Edelsbrunner, H., Harer, J.: Persistent homology \u2013 a survey. Surv. Discrete Comput. Geom. 453, 257\u2013282 (2008)","journal-title":"Surv. Discrete Comput. Geom."},{"key":"2_CR31","unstructured":"Fasy, B.T., Kim, J., Lecci, F., Maria, C., Millman, D.L., Rouvreau, V.: TDA: statistical tools for topological data analysis (2019). https:\/\/CRAN.R-project.org\/package=TDA. R package version 1.6.9"},{"key":"2_CR32","doi-asserted-by":"publisher","unstructured":"Fugacci, U., Scaramuccia, S., Iuricich, F., Floriani, L.D.: Persistent homology: a step-by-step introduction for newcomers. In: Pintore, G., Stanco, F. (eds.) Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, pp. 1\u201310. The Eurographics Association (2016). https:\/\/doi.org\/10.2312\/stag.20161358","DOI":"10.2312\/stag.20161358"},{"issue":"2","key":"2_CR33","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1111\/j.1467-9868.2010.00765.x","volume":"73","author":"M Girolami","year":"2011","unstructured":"Girolami, M., Calderhead, B.: Riemann manifold Langevin and Hamiltonian Monte Carlo methods. J. Roy. Stat. Soc.: Ser. B (Stat. Methodol.) 73(2), 123\u2013214 (2011). https:\/\/doi.org\/10.1111\/j.1467-9868.2010.00765.x","journal-title":"J. Roy. Stat. Soc.: Ser. B (Stat. Methodol.)"},{"key":"2_CR34","unstructured":"Grayson, D.R., Stillman, M.E.: Macaulay2, a software system for research in algebraic geometry (2002)"},{"key":"2_CR35","unstructured":"Greene, P.: De Rham cohomology, connections, and characteristic classes (2009)"},{"key":"2_CR36","doi-asserted-by":"publisher","unstructured":"Hajij, M., Wang, B., Scheidegger, C.E., Rosen, P.: Visual detection of structural changes in time-varying graphs using persistent homology. In: IEEE Pacific Visualization Symposium, pp. 125\u2013134. PacificVis 2018. IEEE Computer Society, USA (2018). https:\/\/doi.org\/10.1109\/PacificVis.2018.00024","DOI":"10.1109\/PacificVis.2018.00024"},{"key":"2_CR37","doi-asserted-by":"publisher","unstructured":"Hartshorne, R.: Algebraic Geometry. Graduate Texts in Mathematics. Springer, New York (1977). https:\/\/doi.org\/10.1007\/978-1-4757-3849-0","DOI":"10.1007\/978-1-4757-3849-0"},{"issue":"3","key":"2_CR38","doi-asserted-by":"publisher","first-page":"P03034","DOI":"10.1088\/1742-5468\/2009\/03\/p03034","volume":"2009","author":"D Horak","year":"2009","unstructured":"Horak, D., Maleti\u0107, S., Rajkovi\u0107, M.: Persistent homology of complex networks. J. Stat. Mech: Theory Exp. 2009(3), P03034 (2009). https:\/\/doi.org\/10.1088\/1742-5468\/2009\/03\/p03034","journal-title":"J. Stat. Mech: Theory Exp."},{"key":"2_CR39","series-title":"Applied Mathematical Sciences","doi-asserted-by":"publisher","DOI":"10.1007\/b97315","volume-title":"Computational Homology","author":"T Kaczynski","year":"2004","unstructured":"Kaczynski, T., Mischaikow, K., Mrozek, M.: Computational Homology. Applied Mathematical Sciences, vol. 157. Springer, New York (2004). https:\/\/doi.org\/10.1007\/b97315"},{"issue":"5","key":"2_CR40","doi-asserted-by":"publisher","first-page":"4466","DOI":"10.1109\/TKDE.2022.3147070","volume":"35","author":"NO Malott","year":"2022","unstructured":"Malott, N.O., Chen, S., Wilsey, P.A.: A survey on the high-performance computation of persistent homology. IEEE Trans. Knowl. Data Eng. 35(5), 4466\u20134484 (2022). https:\/\/doi.org\/10.1109\/TKDE.2022.3147070","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"2_CR41","doi-asserted-by":"crossref","unstructured":"Malott, N.O., Lewis, R.R., Wilsey, P.A.: Homology-separating triangulated Euler characteristic curve. In: IEEE International Conference on Data Mining. ICDM 2022 (2022)","DOI":"10.1109\/ICDM54844.2022.00136"},{"key":"2_CR42","doi-asserted-by":"publisher","unstructured":"Malott, N.O., Wilsey, P.A.: Fast computation of persistent homology with data reduction and data partitioning. In: 2019 IEEE International Conference on Big Data, Big Data 2019, pp. 880\u2013889 (2019). https:\/\/doi.org\/10.1109\/BigData47090.2019.9006572","DOI":"10.1109\/BigData47090.2019.9006572"},{"issue":"2","key":"2_CR43","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1007\/s00454-013-9529-6","volume":"50","author":"K Mischaikow","year":"2013","unstructured":"Mischaikow, K., Nanda, V.: Morse theory for filtrations and efficient computation of persistent homology. Discrete Comput. Geom. 50(2), 330\u2013353 (2013). https:\/\/doi.org\/10.1007\/s00454-013-9529-6","journal-title":"Discrete Comput. Geom."},{"key":"2_CR44","doi-asserted-by":"publisher","unstructured":"Moitra, A., Malott, N.O., Wilsey, P.A.: Persistent homology on streaming data. In: 2020 International Conference on Data Mining Workshops (ICDMW), ICDMW 2020, pp. 636\u2013643. IEEE, USA (2020). https:\/\/doi.org\/10.1109\/ICDMW51313.2020.00090","DOI":"10.1109\/ICDMW51313.2020.00090"},{"key":"2_CR45","unstructured":"Nanda, V.: Discrete Morse theory for filtrations. Ph.D. thesis, Department of Mathematics, Rutgers University (2012). http:\/\/people.maths.ox.ac.uk\/nanda\/source\/Thesis.pdf"},{"key":"2_CR46","doi-asserted-by":"publisher","unstructured":"Otter, N., Porter, M.A., Tillmann, U., Grindrod, P., Harrington, H.A.: A roadmap for the computation of persistent homology. EPJ Data Sci. 6(1) (2017). https:\/\/doi.org\/10.1140\/epjds\/s13688-017-0109-5","DOI":"10.1140\/epjds\/s13688-017-0109-5"},{"key":"2_CR47","doi-asserted-by":"publisher","unstructured":"Pakyuz-Charrier, E., Jessell, M., Giraud, J., Lindsay, M., Ogarko, V.: Topological analysis in Monte Carlo simulation for uncertainty propagation. Solid Earth 10(5), 1663\u20131684 (2019). https:\/\/doi.org\/10.5194\/se-10-1663-2019, https:\/\/se.copernicus.org\/articles\/10\/1663\/2019\/","DOI":"10.5194\/se-10-1663-2019"},{"issue":"6","key":"2_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0066506","volume":"8","author":"G Petri","year":"2013","unstructured":"Petri, G., Scolamiero, M., Donato, I., Vaccarino, F.: Topological strata of weighted complex networks. PLoS One 8(6), 1\u20138 (2013). https:\/\/doi.org\/10.1371\/journal.pone.0066506","journal-title":"PLoS One"},{"key":"2_CR49","doi-asserted-by":"publisher","unstructured":"Pun, C.S., Xia, K., Lee, S.X.: Persistent-homology-based machine learning and its applications - a survey (2018). https:\/\/doi.org\/10.2139\/ssrn.3275996","DOI":"10.2139\/ssrn.3275996"},{"key":"2_CR50","unstructured":"Researchers at The High Performance Computing Laboratory: LHF: Lightweight homology framework (2020). https:\/\/github.com\/wilseypa\/lhf"},{"key":"2_CR51","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.patrec.2014.07.001","volume":"49","author":"E Richardson","year":"2014","unstructured":"Richardson, E., Werman, M.: Efficient classification using the Euler characteristic. Pattern Recogn. Lett. 49, 99\u2013106 (2014). https:\/\/doi.org\/10.1016\/j.patrec.2014.07.001","journal-title":"Pattern Recogn. Lett."},{"key":"2_CR52","unstructured":"Saul, N.: TaDAsets. https:\/\/pypi.org\/project\/tadasets\/"},{"key":"2_CR53","unstructured":"Sens, A.: Topology preserving data reductions for computing persistent homology. Master\u2019s thesis, Department of Electrical Engineering and Computer Science, University of Cincinnati (2021)"},{"key":"2_CR54","doi-asserted-by":"publisher","unstructured":"Singh, G., Memoli, F., Carlsson, G.: Topological methods for the analysis of high dimensional data sets and 3D object recognition. In: Botsch, M., Pajarola, R., Chen, B., Zwicker, M. (eds.) Eurographics Symposium on Point-Based Graphics. The Eurographics Association (2007). https:\/\/doi.org\/10.2312\/SPBG\/SPBG07\/091-100","DOI":"10.2312\/SPBG\/SPBG07\/091-100"},{"key":"2_CR55","doi-asserted-by":"publisher","unstructured":"Singh, R.P., Wilsey, P.A.: Persistence homology of proximity hyper-graphs for higher dimensional big data. In: IEEE International Conference on Big Data, BigData 2022 (2022). https:\/\/doi.org\/10.1109\/BigData55660.2022.10020926","DOI":"10.1109\/BigData55660.2022.10020926"},{"key":"2_CR56","doi-asserted-by":"publisher","unstructured":"Singh, R.P., Wilsey, P.A.: Polytopal complex construction and use in persistent homology. In: IEEE ICDM Workshop on High Dimensional Data Mining, HDM 2022 (2022). https:\/\/doi.org\/10.1109\/ICDMW58026.2022.00087","DOI":"10.1109\/ICDMW58026.2022.00087"},{"key":"2_CR57","doi-asserted-by":"crossref","unstructured":"Sumner, R.W., Popovic, J.: Mesh data from deformation transfer for triangle meshes (2004). https:\/\/people.csail.mit.edu\/sumner\/research\/deftransfer\/data.html","DOI":"10.1145\/1186562.1015736"},{"key":"2_CR58","doi-asserted-by":"publisher","unstructured":"Verma, R.R., Malott, N.O., Wilsey, P.A.: Data reduction and feature isolation for computing persistent homology on high dimensional data. In: Workshop on Applications of Topological Data Analysis to Big Data, pp. 3860\u20133864. IEEE, USA (2021). https:\/\/doi.org\/10.1109\/BigData52589.2021.9671839","DOI":"10.1109\/BigData52589.2021.9671839"},{"key":"2_CR59","series-title":"Mathematics and Visualization","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1007\/978-3-642-23175-9_7","volume-title":"Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications","author":"H Wagner","year":"2012","unstructured":"Wagner, H., Chen, C., Vu\u00e7ini, E.: Efficient computation of persistent homology for cubical data. In: Peikert, R., Hauser, H., Carr, H., Fuchs, R. (eds.) Topological Methods in Data Analysis and Visualization II: Theory, Algorithms, and Applications. Mathematics and Visualization, pp. 91\u2013106. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-23175-9_7"},{"issue":"4\u20135","key":"2_CR60","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1006\/jsco.1999.0328","volume":"29","author":"U Walther","year":"2000","unstructured":"Walther, U.: Algorithmic computation of de Rham cohomology of complements of complex affine varieties. J. Symb. Comput. 29(4\u20135), 795\u2013839 (2000). https:\/\/doi.org\/10.1006\/jsco.1999.0328","journal-title":"J. Symb. Comput."},{"issue":"8","key":"2_CR61","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1002\/cnm.2655","volume":"30","author":"K Xia","year":"2014","unstructured":"Xia, K., Wei, G.W.: Persistent homology analysis of protein structure, flexibility, and folding. Int. J. Numer. Methods Biomed. Eng. 30(8), 814\u2013844 (2014). https:\/\/doi.org\/10.1002\/cnm.2655","journal-title":"Int. J. Numer. Methods Biomed. Eng."},{"key":"2_CR62","doi-asserted-by":"publisher","unstructured":"Zhu, X.: Persistent homology: An introduction and a new text representation for natural language processing. In: Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI 2013, pp. 1953\u20131959. AAAI Press (2013). https:\/\/doi.org\/10.5555\/2540128.2540408","DOI":"10.5555\/2540128.2540408"}],"container-title":["Lecture Notes in Computer Science","Benchmarking, Measuring, and Optimizing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-0316-6_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T19:03:00Z","timestamp":1707850980000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-0316-6_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819703159","9789819703166"],"references-count":62,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-0316-6_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"14 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Bench","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Benchmarking, Measuring and Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sanya","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bench2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.benchcouncil.org\/bench2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"HotCRP","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","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":"11","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":"55% - 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":"4.75","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}