{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:21:37Z","timestamp":1743121297361,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030896560"},{"type":"electronic","value":"9783030896577"}],"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\/978-3-030-89657-7_24","type":"book-chapter","created":{"date-parts":[[2021,10,21]],"date-time":"2021-10-21T21:02:48Z","timestamp":1634850168000},"page":"323-336","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Metric Indexing for Graph Similarity Search"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4202-3692","authenticated-orcid":false,"given":"Franka","family":"Bause","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8651-750X","authenticated-orcid":false,"given":"David B.","family":"Blumenthal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9143-4880","authenticated-orcid":false,"given":"Erich","family":"Schubert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2645-947X","authenticated-orcid":false,"given":"Nils M.","family":"Kriege","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,22]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Beygelzimer, A., Kakade, S.M., Langford, J.: Cover trees for nearest neighbor. In: International Conference Machine Learning, ICML, vol. 148, pp. 97\u2013104 (2006)","DOI":"10.1145\/1143844.1143857"},{"issue":"3","key":"24_CR2","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1109\/TKDE.2017.2772243","volume":"30","author":"DB Blumenthal","year":"2018","unstructured":"Blumenthal, D.B., Gamper, J.: Improved lower bounds for graph edit distance. IEEE Trans. Knowl. Data Eng. 30(3), 503\u2013516 (2018)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"24_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2021.101766","volume":"100","author":"DB Blumenthal","year":"2021","unstructured":"Blumenthal, D.B., Boria, N., Bougleux, S., Brun, L., Gamper, J., Ga\u00fcz\u00e8re, B.: Scalable generalized median graph estimation and its manifold use in bioinformatics, clustering, classification, and indexing. Inf. Syst. 100, 101766 (2021)","journal-title":"Inf. Syst."},{"issue":"1","key":"24_CR4","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1007\/s00778-019-00544-1","volume":"29","author":"DB Blumenthal","year":"2019","unstructured":"Blumenthal, D.B., Boria, N., Gamper, J., Bougleux, S., Brun, L.: Comparing heuristics for graph edit distance computation. VLDB J. 29(1), 419\u2013458 (2019). https:\/\/doi.org\/10.1007\/s00778-019-00544-1","journal-title":"VLDB J."},{"key":"24_CR5","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.patrec.2018.05.002","volume":"134","author":"DB Blumenthal","year":"2020","unstructured":"Blumenthal, D.B., Gamper, J.: On the exact computation of the graph edit distance. Pattern Recogn. Lett. 134, 46\u201357 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"24_CR6","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.patrec.2019.10.028","volume":"129","author":"N Boria","year":"2020","unstructured":"Boria, N., Blumenthal, D.B., Bougleux, S., Brun, L.: Improved local search for graph edit distance. Pattern Recogn. Lett. 129, 19\u201325 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"24_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.patrec.2018.03.032","volume":"134","author":"S Bougleux","year":"2020","unstructured":"Bougleux, S., Ga\u00fcz\u00e8re, B., Blumenthal, D.B., Brun, L.: Fast linear sum assignment with error-correction and no cost constraints. Pattern Recogn. Lett. 134, 37\u201345 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"24_CR8","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972238","volume-title":"Assignment Problems","author":"RE Burkard","year":"2012","unstructured":"Burkard, R.E., Dell\u2019Amico, M., Martello, S.: Assignment Problems. SIAM, Philadelphia (2012)"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Chang, L., Feng, X., Lin, X., Qin, L., Zhang, W., Ouyang, D.: Speeding up GED verification for graph similarity search. In: International Conference Data Engineering, ICDE, pp. 793\u2013804 (2020)","DOI":"10.1109\/ICDE48307.2020.00074"},{"key":"24_CR10","doi-asserted-by":"publisher","first-page":"762","DOI":"10.1016\/j.knosys.2018.10.002","volume":"163","author":"X Chen","year":"2019","unstructured":"Chen, X., Huo, H., Huan, J., Vitter, J.S.: An efficient algorithm for graph edit distance computation. Knowl. Based Syst. 163, 762\u2013775 (2019)","journal-title":"Knowl. Based Syst."},{"key":"24_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-46759-7_1","volume-title":"Similarity Search and Applications","author":"K Gouda","year":"2016","unstructured":"Gouda, K., Arafa, M., Calders, T.: BFST_ED: a novel upper bound computation framework for the graph edit distance. In: Amsaleg, L., Houle, M.E., Schubert, E. (eds.) SISAP 2016. LNCS, vol. 9939, pp. 3\u201319. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46759-7_1"},{"key":"24_CR12","doi-asserted-by":"crossref","unstructured":"Gouda, K., Hassaan, M.: CSI_GED: an efficient approach for graph edit similarity computation. In: International Conference Data Engineering, ICDE, pp. 265\u2013276 (2016)","DOI":"10.1109\/ICDE.2016.7498246"},{"key":"24_CR13","unstructured":"Kim, J., Choi, D., Li, C.: Inves: incremental partitioning-based verification for graph similarity search. In: Extending Database Technology, EDBT, pp. 229\u2013240 (2019)"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Kriege, N.M., Giscard, P., Bause, F., Wilson, R.C.: Computing optimal assignments in linear time for approximate graph matching. In: ICDM, pp. 349\u2013358 (2019)","DOI":"10.1109\/ICDM.2019.00045"},{"key":"24_CR15","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.patcog.2017.07.029","volume":"72","author":"J Lerouge","year":"2017","unstructured":"Lerouge, J., Abu-Aisheh, Z., Raveaux, R., H\u00e9roux, P., Adam, S.: New binary linear programming formulation to compute the graph edit distance. Pattern Recogn. 72, 254\u2013265 (2017)","journal-title":"Pattern Recogn."},{"key":"24_CR16","doi-asserted-by":"crossref","unstructured":"Liang, Y., Zhao, P.: Similarity search in graph databases: A multi-layered indexing approach. In: International Conference Data Engineering, ICDE, pp. 783\u2013794 (2017)","DOI":"10.1109\/ICDE.2017.129"},{"key":"24_CR17","unstructured":"Morris, C., Kriege, N.M., Bause, F., Kersting, K., Mutzel, P., Neumann, M.: TUDataset: a collection of benchmark datasets for learning with graphs. In: ICML 2020 Workshop on Graph Representation Learning and Beyond, GRL+ (2020)"},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Neuhaus, M., Riesen, K., Bunke, H.: Fast suboptimal algorithms for the computation of graph edit distance. In: Structural, Syntactic, and Statistical Pattern Recognition. pp. 163\u2013172, August 2006","DOI":"10.1007\/11815921_17"},{"key":"24_CR19","doi-asserted-by":"crossref","unstructured":"Qin, Z., Bai, Y., Sun, Y.: Ghashing: semantic graph hashing for approximate similarity search in graph databases. In: ACM SIGKDD, pp. 2062\u20132072 (2020)","DOI":"10.1145\/3394486.3403257"},{"issue":"7","key":"24_CR20","doi-asserted-by":"publisher","first-page":"950","DOI":"10.1016\/j.imavis.2008.04.004","volume":"27","author":"K Riesen","year":"2009","unstructured":"Riesen, K., Bunke, H.: Approximate graph edit distance computation by means of bipartite graph matching. Image Vis. Comput. 27(7), 950\u2013959 (2009)","journal-title":"Image Vis. Comput."},{"key":"24_CR21","unstructured":"Schubert, E., Zimek, A.: ELKI: a large open-source library for data analysis - ELKI release 0.7.5 \u201cHeidelberg\u201d. CoRR abs\/1902.03616 (2019)"},{"key":"24_CR22","doi-asserted-by":"crossref","unstructured":"Seidl, T., Kriegel, H.: Optimal multi-step k-nearest neighbor search. In: SIGMOD International Conference Management of Data, pp. 154\u2013165 (1998)","DOI":"10.1145\/276305.276319"},{"key":"24_CR23","doi-asserted-by":"crossref","unstructured":"Serratosa, F., Cort\u00e9s, X., Sol\u00e9-Ribalta, A.: Graph database retrieval based on metric-trees. In: SSPR, pp. 437\u2013447 (2012)","DOI":"10.1007\/978-3-642-34166-3_48"},{"key":"24_CR24","doi-asserted-by":"crossref","unstructured":"Stauffer, M., Tschachtli, T., Fischer, A., Riesen, K.: A survey on applications of bipartite graph edit distance. In: GbRPR, pp. 242\u2013252 (2017)","DOI":"10.1007\/978-3-319-58961-9_22"},{"issue":"3","key":"24_CR25","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1109\/TKDE.2010.28","volume":"24","author":"G Wang","year":"2012","unstructured":"Wang, G., Wang, B., Yang, X., Yu, G.: Efficiently indexing large sparse graphs for similarity search. IEEE Trans. Knowl. Data Eng. 24(3), 440\u2013451 (2012)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"24_CR26","doi-asserted-by":"crossref","unstructured":"Wang, X., Ding, X., Tung, A., Ying, S., Jin, H.: An efficient graph indexing method. In: International Conference Data Engineering, ICDE (2012)","DOI":"10.1109\/ICDE.2012.28"},{"key":"24_CR27","unstructured":"Yianilos, P.N.: Data structures and algorithms for nearest neighbor search in general metric spaces. In: SODA, pp. 311\u2013321 (1993)"},{"issue":"1","key":"24_CR28","doi-asserted-by":"publisher","first-page":"25","DOI":"10.14778\/1687627.1687631","volume":"2","author":"Z Zeng","year":"2009","unstructured":"Zeng, Z., Tung, A.K.H., Wang, J., Feng, J., Zhou, L.: Comparing stars: on approximating graph edit distance. Proc. VLDB Endow. 2(1), 25\u201336 (2009)","journal-title":"Proc. VLDB Endow."},{"issue":"3","key":"24_CR29","doi-asserted-by":"publisher","first-page":"169","DOI":"10.14778\/2732232.2732236","volume":"7","author":"X Zhao","year":"2013","unstructured":"Zhao, X., Xiao, C., Lin, X., Liu, Q., Zhang, W.: A partition-based approach to structure similarity search. Proc. VLDB Endow. 7(3), 169\u2013180 (2013)","journal-title":"Proc. VLDB Endow."},{"key":"24_CR30","doi-asserted-by":"crossref","unstructured":"Zhao, X., Xiao, C., Lin, X., Wang, W.: Efficient graph similarity joins with edit distance constraints. In: International Conference Data Engineering, ICDE (2012)","DOI":"10.1109\/ICDE.2012.91"},{"issue":"4","key":"24_CR31","doi-asserted-by":"publisher","first-page":"964","DOI":"10.1109\/TKDE.2014.2349924","volume":"27","author":"W Zheng","year":"2015","unstructured":"Zheng, W., Zou, L., Lian, X., Wang, D., Zhao, D.: Efficient graph similarity search over large graph databases. IEEE Trans. Knowl. Data Eng. 27(4), 964\u2013978 (2015)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Lecture Notes in Computer Science","Similarity Search and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-89657-7_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,21]],"date-time":"2021-10-21T21:12:51Z","timestamp":1634850771000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-89657-7_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030896560","9783030896577"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-89657-7_24","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":"22 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SISAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Similarity Search and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dortmund","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","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":"29 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 October 2021","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":"sisap2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sisap.org\/2021\/","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":"50","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":"23","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":"5","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":"46% - 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":"3,8","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":"3,2","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)"}}]}}