{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:15:55Z","timestamp":1742912155882,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031069802"},{"type":"electronic","value":"9783031069819"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-06981-9_7","type":"book-chapter","created":{"date-parts":[[2022,5,30]],"date-time":"2022-05-30T19:02:40Z","timestamp":1653937360000},"page":"113-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Impact of\u00a0the\u00a0Characteristics of\u00a0Multi-source Entity Matching Tasks on\u00a0the\u00a0Performance of\u00a0Active Learning Methods"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1783-2482","authenticated-orcid":false,"given":"Anna","family":"Primpeli","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2367-0237","authenticated-orcid":false,"given":"Christian","family":"Bizer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"7_CR1","unstructured":"Achichi, M., Cheatham, M., et al.: Results of the ontology alignment evaluation initiative 2017. In: Proceedings of OM 2017\u201312th ISWC Workshop on Ontology Matching, pp. 61\u2013113 (2017)"},{"issue":"11","key":"7_CR2","first-page":"1114","volume":"6","author":"K Bellare","year":"2013","unstructured":"Bellare, K., Curino, C., Machanavajihala, A., et al.: WOO: a scalable and multi-tenant platform for continuous knowledge base synthesis. PVLDB 6(11), 1114\u20131125 (2013)","journal-title":"PVLDB"},{"key":"7_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1007\/978-3-030-28730-6_5","volume-title":"Advances in Databases and Information Systems","author":"X Chen","year":"2019","unstructured":"Chen, X., Xu, Y., Broneske, D., Durand, G.C., Zoun, R., Saake, G.: Heterogeneous committee-based active learning for entity resolution (HeALER). In: Welzer, T., Eder, J., Podgorelec, V., Kami\u0161ali\u0107 Latifi\u0107, A. (eds.) ADBIS 2019. LNCS, vol. 11695, pp. 69\u201385. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-28730-6_5"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Christen, P.: Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Data-Centric Systems and Applications (2012)","DOI":"10.1007\/978-3-642-31164-2"},{"issue":"6","key":"7_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3418896","volume":"53","author":"V Christophides","year":"2020","unstructured":"Christophides, V., Efthymiou, V., et al.: An overview of end-to-end entity resolution for big data. ACM Comput. Surv. (CSUR) 53(6), 1\u201342 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"1","key":"7_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TKDE.2007.250581","volume":"19","author":"A Elmagarmid","year":"2007","unstructured":"Elmagarmid, A., Ipeirotis, P., et al.: Duplicate record detection: a survey. IEEE Trans. Knowl. Data Eng. 19(1), 1\u201316 (2007)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"7_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/978-3-642-21064-8_8","volume-title":"The Semanic Web: Research and Applications","author":"A Ferrara","year":"2011","unstructured":"Ferrara, A., Montanelli, S., Noessner, J., Stuckenschmidt, H.: Benchmarking matching applications on the semantic web. In: Antoniou, G., et al. (eds.) ESWC 2011. LNCS, vol. 6644, pp. 108\u2013122. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-21064-8_8"},{"key":"7_CR8","unstructured":"Halevy, A., Rajaraman, A., Ordille, J.: Data integration: the teenage years. In: Proceedings of VLD, pp. 9\u201316 (2006)"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Heath, T., Bizer, C.: Linked Data: Evolving the Web Into a Global Data Space. Synthesis Lectures on the Semantic Web. Morgan & Claypool Publishers (2011)","DOI":"10.1007\/978-3-031-79432-2"},{"issue":"2","key":"7_CR10","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1109\/TBDATA.2016.2637378","volume":"6","author":"K Hildebrandt","year":"2020","unstructured":"Hildebrandt, K., Panse, F., et al.: Large-scale data pollution with Apache spark. IEEE Trans. Big Data 6(2), 396\u2013411 (2020)","journal-title":"IEEE Trans. Big Data"},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Huang, J., Hu, W., Li, H., Qu, Y.: Automated comparative table generation for facilitating human intervention in multi-entity resolution. In: Proceedings of SIGIR, pp. 585\u2013594 (2018)","DOI":"10.1145\/3209978.3210021"},{"issue":"1","key":"7_CR12","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/s13740-012-0015-8","volume":"2","author":"E Ioannou","year":"2013","unstructured":"Ioannou, E., Rassadko, N., Velegrakis, Y.: On generating benchmark data for entity matching. J. Data Semant. 2(1), 37\u201356 (2013)","journal-title":"J. Data Semant."},{"key":"7_CR13","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.websem.2013.06.001","volume":"23","author":"R Isele","year":"2013","unstructured":"Isele, R., Bizer, C.: Active learning of expressive linkage rules using genetic programming. J. Web Semant. 23, 2\u201315 (2013)","journal-title":"J. Web Semant."},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Kasai, J., Qian, K., et al.: Low-resource deep entity resolution with transfer and active learning. In: Proceedings of ACL, pp. 5851\u20135861 (2019)","DOI":"10.18653\/v1\/P19-1586"},{"key":"7_CR15","first-page":"1581","volume":"13","author":"P Konda","year":"2016","unstructured":"Konda, P., et al.: Magellan: toward building entity matching management systems over data science stacks. PVLDB 13, 1581\u20131584 (2016)","journal-title":"PVLDB"},{"key":"7_CR16","unstructured":"Konyushkova, K., Raphael, S., Fua, P.: Learning active learning from data. In: Proceedings of NIPS, p. 4228\u20134238 (2017)"},{"issue":"1\u20132","key":"7_CR17","doi-asserted-by":"publisher","first-page":"484","DOI":"10.14778\/1920841.1920904","volume":"3","author":"H K\u00f6pcke","year":"2010","unstructured":"K\u00f6pcke, H., Thor, A., Rahm, E.: Evaluation of entity resolution approaches on real-world match problems. VLDB Endow. 3(1\u20132), 484\u2013493 (2010)","journal-title":"VLDB Endow."},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Meduri, V., Popa, L., et al.: A comprehensive benchmark framework for active learning methods in entity matching. In: Proceedings of SIGMOD, pp. 1133\u20131147 (2020)","DOI":"10.1145\/3318464.3380597"},{"issue":"2","key":"7_CR19","doi-asserted-by":"publisher","first-page":"125","DOI":"10.14778\/2735471.2735474","volume":"8","author":"B Mozafari","year":"2014","unstructured":"Mozafari, B., Sarkar, P., Franklin, M., Jordan, M., Madden, S.: Scaling up crowd-sourcing to very large datasets: a case for active learning. VLDB Endow. 8(2), 125\u2013136 (2014)","journal-title":"VLDB Endow."},{"key":"7_CR20","doi-asserted-by":"publisher","first-page":"107729","DOI":"10.1016\/j.knosys.2021.107729","volume":"236","author":"Y Nafa","year":"2022","unstructured":"Nafa, Y., et al.: Active deep learning on entity resolution by risk sampling. Knowl.-Based Syst. 236, 107729 (2022)","journal-title":"Knowl.-Based Syst."},{"issue":"3","key":"7_CR21","doi-asserted-by":"publisher","first-page":"419","DOI":"10.3233\/SW-150210","volume":"8","author":"M Nentwig","year":"2017","unstructured":"Nentwig, M., Hartung, M., Ngonga Ngomo, A.C., Rahm, E.: A survey of current link discovery frameworks. Semant. Web 8(3), 419\u2013436 (2017)","journal-title":"Semant. Web"},{"key":"7_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/978-3-642-30284-8_17","volume-title":"The Semantic Web: Research and Applications","author":"A-C Ngonga Ngomo","year":"2012","unstructured":"Ngonga Ngomo, A.-C., Lyko, K.: EAGLE: efficient active learning of link specifications using genetic programming. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 149\u2013163. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-30284-8_17"},{"issue":"2","key":"7_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-01878-7","volume":"16","author":"G Papadakis","year":"2021","unstructured":"Papadakis, G., Ioannou, E., Thanos, E., Palpanas, T.: The four generations of entity resolution. Synthesis Lect. Data Manage. 16(2), 1\u2013170 (2021)","journal-title":"Synthesis Lect. Data Manage."},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Primpeli, A., Bizer, C.: Profiling entity matching benchmark tasks. In: Proceedings of CIKM, pp. 3101\u20133108 (2020)","DOI":"10.1145\/3340531.3412781"},{"key":"7_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1007\/978-3-030-88361-4_11","volume-title":"The Semantic Web \u2013 ISWC 2021","author":"A Primpeli","year":"2021","unstructured":"Primpeli, A., Bizer, C.: Graph-boosted active learning for multi-source entity resolution. In: Hotho, A., et al. (eds.) ISWC 2021. LNCS, vol. 12922, pp. 182\u2013199. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88361-4_11"},{"key":"7_CR26","doi-asserted-by":"crossref","unstructured":"Qian, K., Popa, L., Sen, P.: Active learning for large-scale entity resolution. In: Proceedings of CIKM, pp. 1379\u20131388 (2017)","DOI":"10.1145\/3132847.3132949"},{"key":"7_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1007\/978-3-319-66917-5_19","volume-title":"Advances in Databases and Information Systems","author":"A Saeedi","year":"2017","unstructured":"Saeedi, A., Peukert, E., Rahm, E.: Comparative evaluation of distributed clustering schemes for multi-source entity resolution. In: Kirikova, M., N\u00f8rv\u00e5g, K., Papadopoulos, G.A. (eds.) ADBIS 2017. LNCS, vol. 10509, pp. 278\u2013293. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-66917-5_19"},{"key":"7_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/978-3-319-25007-6_22","volume-title":"The Semantic Web - ISWC 2015","author":"T Saveta","year":"2015","unstructured":"Saveta, T., Daskalaki, E., Flouris, G., Fundulaki, I., Herschel, M., Ngomo, A.-C.N.: LANCE: piercing to the heart of instance matching tools. In: ISWC 2015. LNCS, vol. 9366, pp. 375\u2013391. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-25007-6_22"},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Settles, B.: Active Learning: Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers (2012)","DOI":"10.1007\/978-3-031-01560-1"},{"key":"7_CR30","doi-asserted-by":"crossref","unstructured":"Shen, W., DeRose, P., Vu, L., et al.: Source-aware entity matching: a compositional approach. In: Proceedings of ICDE, pp. 196\u2013205 (2007)","DOI":"10.1109\/ICDE.2007.367865"},{"key":"7_CR31","unstructured":"Sherif, M.A., Dre\u00dfler, K., Ngomo, A.C.N.: LIGON-link discovery with noisy oracles. In: Proceedings of Ontology Matching Workshop (ISWC), pp. 48\u201359 (2020)"},{"key":"7_CR32","unstructured":"Thirumuruganathan, S., Parambath, S.A.P., et al.: Reuse and adaptation for entity resolution through transfer learning. arXiv preprint arXiv:1809.11084 (2018)"},{"issue":"7","key":"7_CR33","first-page":"12","volume":"34","author":"Y Ye","year":"2019","unstructured":"Ye, Y., Talburt, J.: Generating synthetic data to support entity resolution education and research. J. Comput. Sci. Coll. 34(7), 12\u201319 (2019)","journal-title":"J. Comput. Sci. Coll."}],"container-title":["Lecture Notes in Computer Science","The Semantic Web"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-06981-9_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:16:23Z","timestamp":1710260183000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-06981-9_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031069802","9783031069819"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-06981-9_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"31 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ESWC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Semantic Web Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hersonissos","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 May 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 June 2022","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":"esws2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2022.eswc-conferences.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":"66","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":"46","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":"36","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":"70% - 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":"1.3","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)"}}]}}