{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T12:23:06Z","timestamp":1755692586390,"version":"3.40.3"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030742508"},{"type":"electronic","value":"9783030742515"}],"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\/978-3-030-74251-5_28","type":"book-chapter","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T15:20:40Z","timestamp":1618240840000},"page":"350-361","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Ising-Based Louvain Method: Clustering Large Graphs with Specialized Hardware"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5108-8626","authenticated-orcid":false,"given":"Pouya Rezazadeh","family":"Kalehbasti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1442-3077","authenticated-orcid":false,"given":"Hayato","family":"Ushijima-Mwesigwa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avradip","family":"Mandal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3146-4003","authenticated-orcid":false,"given":"Indradeep","family":"Ghosh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,13]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","first-page":"48","DOI":"10.3389\/fphy.2019.00048","volume":"7","author":"M Aramon","year":"2019","unstructured":"Aramon, M., Rosenberg, G., Valiante, E., Miyazawa, T., Tamura, H., Katzgraber, H.G.: Physics-inspired optimization for quadratic unconstrained problems using a digital annealer. Front. Phys. 7, 48 (2019)","journal-title":"Front. Phys."},{"key":"28_CR2","unstructured":"Bian, Z., Chudak, F., Macready, W.G., Rose, G.: The Ising model: teaching an old problem new tricks. D-wave Syst. 2 (2010)"},{"issue":"10","key":"28_CR3","doi-asserted-by":"publisher","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"2008","author":"VD Blondel","year":"2008","unstructured":"Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech: Theory Exp. 2008(10), P10008 (2008)","journal-title":"J. Stat. Mech: Theory Exp."},{"key":"28_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/978-3-030-44584-3_9","volume-title":"Advances in Intelligent Data Analysis XVIII","author":"E Cohen","year":"2020","unstructured":"Cohen, E., Mandal, A., Ushijima-Mwesigwa, H., Roy, A.: Ising-based consensus clustering on specialized hardware. In: Berthold, M.R., Feelders, A., Krempl, G. (eds.) IDA 2020. LNCS, vol. 12080, pp. 106\u2013118. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-44584-3_9"},{"key":"28_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/978-3-030-58942-4_9","volume-title":"Integration of Constraint Programming, Artificial Intelligence, and Operations Research","author":"E Cohen","year":"2020","unstructured":"Cohen, E., Senderovich, A., Beck, J.C.: An Ising framework for constrained clustering on special purpose hardware. In: Hebrard, E., Musliu, N. (eds.) CPAIOR 2020. LNCS, vol. 12296, pp. 130\u2013147. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58942-4_9"},{"issue":"3\u20135","key":"28_CR6","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.physrep.2009.11.002","volume":"486","author":"S Fortunato","year":"2010","unstructured":"Fortunato, S.: Community detection in graphs. Phys. Rep. 486(3\u20135), 75\u2013174 (2010)","journal-title":"Phys. Rep."},{"key":"28_CR7","unstructured":"Fujitsu: Digital annealer. https:\/\/www.fujitsu.com\/global\/services\/business-services\/digital-annealer\/"},{"issue":"12","key":"28_CR8","doi-asserted-by":"publisher","first-page":"7821","DOI":"10.1073\/pnas.122653799","volume":"99","author":"M Girvan","year":"2002","unstructured":"Girvan, M., Newman, M.E.: Community structure in social and biological networks. Proc. Natl. Acad. Sci. 99(12), 7821\u20137826 (2002)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"7028","key":"28_CR9","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1038\/nature03288","volume":"433","author":"R Guimera","year":"2005","unstructured":"Guimera, R., Amaral, L.A.N.: Functional cartography of complex metabolic networks. Nature 433(7028), 895\u2013900 (2005)","journal-title":"Nature"},{"key":"28_CR10","unstructured":"Hagberg, A., Swart, P., S Chult, D.: Exploring network structure, dynamics, and function using network. Technical report, Los Alamos National Lab. (LANL), Los Alamos, NM (United States) (2008)"},{"key":"28_CR11","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.jnca.2018.02.011","volume":"108","author":"MA Javed","year":"2018","unstructured":"Javed, M.A., Younis, M.S., Latif, S., Qadir, J., Baig, A.: Community detection in networks: a multidisciplinary review. J. Netw. Comput. Appl. 108, 87\u2013111 (2018)","journal-title":"J. Netw. Comput. Appl."},{"issue":"3","key":"28_CR12","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/BF02289588","volume":"32","author":"SC Johnson","year":"1967","unstructured":"Johnson, S.C.: Hierarchical clustering schemes. Psychometrika 32(3), 241\u2013254 (1967)","journal-title":"Psychometrika"},{"key":"28_CR13","volume-title":"The Stanford GraphBase: a platform for combinatorial computing","author":"DE Knuth","year":"1993","unstructured":"Knuth, D.E.: The Stanford GraphBase: a platform for combinatorial computing. ACM Press, New York (1993)"},{"issue":"7084","key":"28_CR14","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1038\/nature04670","volume":"440","author":"NJ Krogan","year":"2006","unstructured":"Krogan, N.J., et al.: Global landscape of protein complexes in the yeast saccharomyces cerevisiae. Nature 440(7084), 637\u2013643 (2006)","journal-title":"Nature"},{"issue":"2","key":"28_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11128-017-1809-2","volume":"17","author":"V Kumar","year":"2018","unstructured":"Kumar, V., Bass, G., Tomlin, C., Dulny, J.: Quantum annealing for combinatorial clustering. Quantum Inf. Process. 17(2), 1\u201314 (2018). https:\/\/doi.org\/10.1007\/s11128-017-1809-2","journal-title":"Quantum Inf. Process."},{"issue":"4","key":"28_CR16","doi-asserted-by":"publisher","first-page":"046110","DOI":"10.1103\/PhysRevE.78.046110","volume":"78","author":"A Lancichinetti","year":"2008","unstructured":"Lancichinetti, A., Fortunato, S., Radicchi, F.: Benchmark graphs for testing community detection algorithms. Phys. Rev. E 78(4), 046110 (2008)","journal-title":"Phys. Rev. E"},{"key":"28_CR17","unstructured":"Leskovec, J., Krevl, A.: SNAP Datasets: Stanford large network dataset collection (2014). http:\/\/snap.stanford.edu\/data"},{"key":"28_CR18","unstructured":"Liu, X., Ushijima-Mwesigwa, H., Mandal, A., Upadhyay, S., Safro, I., Roy, A.: On modeling local search with special-purpose combinatorial optimization hardware. arXiv preprint arXiv:1911.09810 (2019)"},{"issue":"1","key":"28_CR19","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/S0095-8956(73)80006-1","volume":"14","author":"GH Meredith","year":"1973","unstructured":"Meredith, G.H.: Regular n-valent n-connected non Hamiltonian non-n-edge-colorable graphs. J. Comb. Theory Ser. B 14(1), 55\u201360 (1973)","journal-title":"J. Comb. Theory Ser. B"},{"key":"28_CR20","doi-asserted-by":"crossref","unstructured":"Naghsh, Z., Javad-Kalbasi, M., Valaee, S.: Digitally annealed solution for the maximum clique problem with critical application in cellular v2x. In: ICC, pp. 1\u20137. IEEE (2019)","DOI":"10.1109\/ICC.2019.8761634"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Negre, C.F., Ushijima-Mwesigwa, H., Mniszewski, S.M.: Detecting multiple communities using quantum annealing on the d-wave system. Plos one 15(2), e0227538 (2020)","DOI":"10.1371\/journal.pone.0227538"},{"issue":"2","key":"28_CR22","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1140\/epjb\/e2004-00124-y","volume":"38","author":"MEJ Newman","year":"2004","unstructured":"Newman, M.E.J.: Detecting community structure in networks. Eur. Phys. J. B 38(2), 321\u2013330 (2004). https:\/\/doi.org\/10.1140\/epjb\/e2004-00124-y","journal-title":"Eur. Phys. J. B"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Newman, M.E.: Spectral methods for community detection and graph partitioning. Phys. Rev. E 88(4), 042822 (2013)","DOI":"10.1103\/PhysRevE.88.042822"},{"key":"28_CR24","unstructured":"Newman, M.E.: Community detection in networks: modularity optimization and maximum likelihood are equivalent. arXiv preprint arXiv:1606.02319 (2016)"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Newman, M.E.: Equivalence between modularity optimization and maximum likelihood methods for community detection. Phys. Rev. E 94(5), 052315 (2016)","DOI":"10.1103\/PhysRevE.94.052315"},{"key":"28_CR26","doi-asserted-by":"crossref","unstructured":"Newman, M.E., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69(2), 026113 (2004)","DOI":"10.1103\/PhysRevE.69.026113"},{"key":"28_CR27","doi-asserted-by":"crossref","unstructured":"Palla, G., Der\u00e9nyi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex networks in nature and society. Nature 435(7043), 814\u2013818 (2005)","DOI":"10.1038\/nature03607"},{"key":"28_CR28","doi-asserted-by":"crossref","unstructured":"Rahman, M.T., Han, S., Tadayon, N., Valaee, S.: Ising model formulation of outlier rejection, with application in Wifi based positioning. In: ICASSP, pp. 4405\u20134409. IEEE (2019)","DOI":"10.1109\/ICASSP.2019.8683807"},{"key":"28_CR29","doi-asserted-by":"crossref","unstructured":"Reichardt, J., Bornholdt, S.: Detecting fuzzy community structures in complex networks with a Potts model. Phys. Rev. Lett. 93(21), 218701 (2004)","DOI":"10.1103\/PhysRevLett.93.218701"},{"key":"28_CR30","doi-asserted-by":"crossref","unstructured":"Ruan, Y., Fuhry, D., Parthasarathy, S.: Efficient community detection in large networks using content and links. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 1089\u20131098 (2013)","DOI":"10.1145\/2488388.2488483"},{"key":"28_CR31","unstructured":"Shaydulin, R., Ushijima-Mwesigwa, H., Safro, I., Mniszewski, S., Alexeev, Y.: Community detection across emerging quantum architectures. arXiv preprint arXiv:1810.07765 (2018)"},{"issue":"9","key":"28_CR32","doi-asserted-by":"publisher","first-page":"1900029","DOI":"10.1002\/qute.201900029","volume":"2","author":"R Shaydulin","year":"2019","unstructured":"Shaydulin, R., Ushijima-Mwesigwa, H., Safro, I., Mniszewski, S., Alexeev, Y.: Network community detection on small quantum computers. Adv. Quantum Technol. 2(9), 1900029 (2019)","journal-title":"Adv. Quantum Technol."},{"issue":"1","key":"28_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-019-41695-z","volume":"9","author":"VA Traag","year":"2019","unstructured":"Traag, V.A., Waltman, L., van Eck, N.J.: From Louvain to Leiden: guaranteeing well-connected communities. Sci. Rep. 9(1), 1\u201312 (2019)","journal-title":"Sci. Rep."},{"key":"28_CR34","doi-asserted-by":"crossref","unstructured":"Ushijima-Mwesigwa, H., Negre, C.F., Mniszewski, S.M.: Graph partitioning using quantum annealing on the d-wave system. In: Proceedings of the Second International Workshop on Post Moores Era Supercomputing, pp. 22\u201329 (2017)","DOI":"10.1145\/3149526.3149531"},{"key":"28_CR35","unstructured":"Ushijima-Mwesigwa, H., Shaydulin, R., Negre, C.F., Mniszewski, S.M., Alexeev, Y., Safro, I.: Multilevel combinatorial optimization across quantum architectures. arXiv preprint arXiv:1910.09985 (2019)"},{"issue":"4","key":"28_CR36","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1086\/jar.33.4.3629752","volume":"33","author":"WW Zachary","year":"1977","unstructured":"Zachary, W.W.: An information flow model for conflict and fission in small groups. J. Anthropol. Res. 33(4), 452\u2013473 (1977)","journal-title":"J. Anthropol. Res."}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XIX"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-74251-5_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T00:36:34Z","timestamp":1619310994000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-74251-5_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030742508","9783030742515"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-74251-5_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"13 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","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":"26 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ida2021.org\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"113","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":"35","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":"31% - 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","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":"The conference was held online due to the COVID-19 pandemic","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)"}}]}}