{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:55:38Z","timestamp":1743036938676,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030109271"},{"type":"electronic","value":"9783030109288"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-10928-8_10","type":"book-chapter","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T08:19:39Z","timestamp":1548317979000},"page":"158-174","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Semi-supervised Blockmodelling with Pairwise Guidance"],"prefix":"10.1007","author":[{"given":"Mohadeseh","family":"Ganji","sequence":"first","affiliation":[]},{"given":"Jeffrey","family":"Chan","sequence":"additional","affiliation":[]},{"given":"Peter J.","family":"Stuckey","sequence":"additional","affiliation":[]},{"given":"James","family":"Bailey","sequence":"additional","affiliation":[]},{"given":"Christopher","family":"Leckie","sequence":"additional","affiliation":[]},{"given":"Kotagiri","family":"Ramamohanarao","sequence":"additional","affiliation":[]},{"given":"Laurence","family":"Park","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,23]]},"reference":[{"issue":"1","key":"10_CR1","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.csda.2006.11.006","volume":"52","author":"MW Berry","year":"2007","unstructured":"Berry, M.W., Browne, M., Langville, A.N., Pauca, V.P., Plemmons, R.J.: Algorithms and applications for approximate nonnegative matrix factorization. Comput. Stat. Data Anal. 52(1), 155\u2013173 (2007)","journal-title":"Comput. Stat. Data Anal."},{"issue":"10","key":"10_CR2","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."},{"issue":"1","key":"10_CR3","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s13278-014-0155-y","volume":"4","author":"J Chan","year":"2014","unstructured":"Chan, J., Lam, S., Hayes, C.: Generalised blockmodelling of social and relational networks using evolutionary computing. Soc. Netw. Anal. Mining 4(1), 155 (2014)","journal-title":"Soc. Netw. Anal. Mining"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Chan, J., Leckie, C., Bailey, J., Ramamohanarao, K.: TRIBAC: discovering interpretable clusters and latent structures in graphs. In: Proceedings of the 15th IEEE International Conference on Data Mining, pp. 737\u2013742 (2015)","DOI":"10.1109\/ICDM.2014.118"},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Chan, J., Liu, W., Kan, A., Leckie, C., Bailey, J., Ramamohanarao, K.: Discovering latent blockmodels in sparse and noisy graphs using non-negative matrix factorisation. In: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, pp. 811\u2013816. ACM (2013)","DOI":"10.1145\/2505515.2505595"},{"issue":"09","key":"10_CR6","doi-asserted-by":"publisher","first-page":"P09008","DOI":"10.1088\/1742-5468\/2005\/09\/P09008","volume":"2005","author":"L Danon","year":"2005","unstructured":"Danon, L., Diaz-Guilera, A., Duch, J., Arenas, A.: Comparing community structure identification. J. Stat. Mech.: Theory Exp. 2005(09), P09008 (2005)","journal-title":"J. Stat. Mech.: Theory Exp."},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Davidson, I., Ravi, S.: Intractability and clustering with constraints. In: Proceedings of the 24th International Conference on Machine Learning, pp. 201\u2013208. ACM (2007)","DOI":"10.1145\/1273496.1273522"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Davidson, I., Ravi, S., Shamis, L.: A SAT-based framework for efficient constrained clustering. In: Proceedings of SIAM International Conference on Data Mining, pp. 94\u2013105 (2010)","DOI":"10.1137\/1.9781611972801.9"},{"key":"10_CR9","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.artint.2015.05.006","volume":"244","author":"K-C Duong","year":"2017","unstructured":"Duong, K.-C., Vrain, C., et al.: Constrained clustering by constraint programming. Artif. Intell. 244, 70\u201394 (2017)","journal-title":"Artif. Intell."},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Eaton, E., Mansbach, R.: A spin-glass model for semi-supervised community detection. In: AAAI, pp. 900\u2013906 (2012)","DOI":"10.1609\/aaai.v26i1.8320"},{"key":"10_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1007\/3-540-45061-0_64","volume-title":"Automata, Languages and Programming","author":"J Fiala","year":"2003","unstructured":"Fiala, J., Paulusma, D.: The computational complexity of the role assignment problem. In: Baeten, J.C.M., Lenstra, J.K., Parrow, J., Woeginger, G.J. (eds.) ICALP 2003. LNCS, vol. 2719, pp. 817\u2013828. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/3-540-45061-0_64"},{"issue":"3","key":"10_CR12","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), 75\u2013174 (2010)","journal-title":"Phys. Rep."},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Ganji, M., Bailey, J., Stuckey, P.J.: Lagrangian constrained clustering. In: Proceedings of SIAM International Conference on Data Mining, pp. 288\u2013296. SIAM (2016)","DOI":"10.1137\/1.9781611974348.33"},{"key":"10_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1007\/978-3-319-66158-2_31","volume-title":"Principles and Practice of Constraint Programming","author":"M Ganji","year":"2017","unstructured":"Ganji, M., Bailey, J., Stuckey, P.J.: A declarative approach to constrained community detection. In: Beck, J.C. (ed.) CP 2017. LNCS, vol. 10416, pp. 477\u2013494. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66158-2_31"},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Ganji, M., Bailey, J., Stuckey, P.J.: Lagrangian constrained community detection. In: Proceedings of AAAI (2018, to appear)","DOI":"10.1609\/aaai.v32i1.11753"},{"key":"10_CR16","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1137\/1.9781611975321.3","volume-title":"Proceedings of the 2018 SIAM International Conference on Data Mining","author":"Mohadeseh Ganji","year":"2018","unstructured":"Ganji, M., et al.: Image constrained blockmodelling: a constraint programming approach. In: Proceedings of SIAM International Conference on Data Mining (2018, to appear)"},{"issue":"1","key":"10_CR17","doi-asserted-by":"publisher","first-page":"016107","DOI":"10.1103\/PhysRevE.83.016107","volume":"83","author":"B Karrer","year":"2011","unstructured":"Karrer, B., Newman, M.E.: Stochastic blockmodels and community structure in networks. Phys. Rev. E 83(1), 016107 (2011)","journal-title":"Phys. Rev. E"},{"key":"10_CR18","unstructured":"Klein, D., Kamvar, S.D., Manning, C.D.: From instance-level constraints to space-level constraints: making the most of prior knowledge in data clustering. Technical report, Stanford (2002)"},{"issue":"3","key":"10_CR19","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s10115-009-0255-6","volume":"24","author":"B Long","year":"2010","unstructured":"Long, B., Zhang, Z., Philip, S.Y.: A general framework for relation graph clustering. Knowl. Inf. Syst. 24(3), 393\u2013413 (2010)","journal-title":"Knowl. Inf. Syst."},{"issue":"2","key":"10_CR20","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1140\/epjb\/e2007-00340-y","volume":"60","author":"J Reichardt","year":"2007","unstructured":"Reichardt, J., White, D.R.: Role models for complex networks. Eur. Phys. J. B-Condens. Matter Complex Syst. 60(2), 217\u2013224 (2007)","journal-title":"Eur. Phys. J. B-Condens. Matter Complex Syst."},{"issue":"3","key":"10_CR21","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1007\/s10618-010-0181-y","volume":"22","author":"F Wang","year":"2011","unstructured":"Wang, F., Li, T., Wang, X., Zhu, S., Ding, C.: Community discovery using nonnegative matrix factorization. Data Mining Knowl. Discov. 22(3), 493\u2013521 (2011)","journal-title":"Data Mining Knowl. Discov."},{"key":"10_CR22","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511815478","volume-title":"Social Network Analysis: Methods and Applications","author":"S Wasserman","year":"1994","unstructured":"Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications, vol. 8. Cambridge University Press, Cambridge (1994)"},{"key":"10_CR23","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yeung, D.-Y.: Overlapping community detection via bounded nonnegative matrix tri-factorization. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 606\u2013614. ACM (2012)","DOI":"10.1145\/2339530.2339629"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-10928-8_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T01:05:46Z","timestamp":1705885546000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-10928-8_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030109271","9783030109288"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-10928-8_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dublin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ireland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ecmlpkdd2018.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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"535","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":"131","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":"17","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":"24% - 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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}