{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:36:10Z","timestamp":1750221370700,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,12,5]],"date-time":"2017-12-05T00:00:00Z","timestamp":1512432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,12,5]]},"DOI":"10.1145\/3148055.3148064","type":"proceedings-article","created":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T20:03:47Z","timestamp":1512158627000},"page":"237-246","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["DIMSpan"],"prefix":"10.1145","author":[{"given":"Andr\u00e9","family":"Petermann","sequence":"first","affiliation":[{"name":"University of Leipzig &amp; ScaDS Dresden\/Leipzig, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Junghanns","sequence":"additional","affiliation":[{"name":"University of Leipzig &amp; ScaDS Dresden\/Leipzig, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erhard","family":"Rahm","sequence":"additional","affiliation":[{"name":"University of Leipzig &amp; ScaDS Dresden\/Leipzig, Leipzig, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,12,5]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/2677098"},{"key":"e_1_3_2_1_2_1","volume-title":"Reconnaissance de Formes et Intelligence Artificielle (RFIA)","author":"Aridhi S.","year":"2014","unstructured":"S. Aridhi , L. D'Orazio , M. Maddouri , and E. Mephu . A novel mapreduce-based approach for distributed frequent subgraph mining . In Reconnaissance de Formes et Intelligence Artificielle (RFIA) , 2014 . S. Aridhi, L. D'Orazio, M. Maddouri, and E. Mephu. A novel mapreduce-based approach for distributed frequent subgraph mining. In Reconnaissance de Formes et Intelligence Artificielle (RFIA), 2014."},{"issue":"3","key":"e_1_3_2_1_3_1","first-page":"608","article-title":"An iterative mapreduce based frequent subgraph mining algorithm. Knowledge and Data Engineering","volume":"27","author":"Bhuiyan M. A.","year":"2015","unstructured":"M. A. Bhuiyan and M. Al Hasan . An iterative mapreduce based frequent subgraph mining algorithm. Knowledge and Data Engineering , IEEE Transactions on , 27 ( 3 ): 608 -- 620 , 2015 . M. A. Bhuiyan and M. Al Hasan. An iterative mapreduce based frequent subgraph mining algorithm. Knowledge and Data Engineering, IEEE Transactions on, 27(3):608--620, 2015.","journal-title":"IEEE Transactions on"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/844380.844706"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/1786574.1786663"},{"key":"e_1_3_2_1_6_1","volume-title":"Apache flink: Stream and batch processing in a single engine. Data Engineering, page 28","author":"Carbone P.","year":"2015","unstructured":"P. Carbone , A. Katsifodimos , S. Ewen , V. Markl , S. Haridi , and K. Tzoumas . Apache flink: Stream and batch processing in a single engine. Data Engineering, page 28 , 2015 . P. Carbone, A. Katsifodimos, S. Ewen, V. Markl, S. Haridi, and K. Tzoumas. Apache flink: Stream and batch processing in a single engine. Data Engineering, page 28, 2015."},{"key":"e_1_3_2_1_7_1","volume-title":"N-quads: Extending n-triples with context. W3C Recommendation","author":"Cyganiak R.","year":"2008","unstructured":"R. Cyganiak , A. Harth , and A. Hogan . N-quads: Extending n-triples with context. W3C Recommendation , 2008 . R. Cyganiak, A. Harth, and A. Hogan. N-quads: Extending n-triples with context. W3C Recommendation, 2008."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732286.2732289"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2382936.2383055"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/951949.952101"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.5555\/645804.669817"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0269888912000331"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2980523.2980527"},{"key":"e_1_3_2_1_15_1","first-page":"1","volume-title":"BigMine","author":"Kessl R.","year":"2014","unstructured":"R. Kessl , N. Talukder , P. Anchuri , and M. Zaki . Parallel graph mining with gpus . In BigMine , pages 1 -- 16 , 2014 . R. Kessl, N. Talukder, P. Anchuri, and M. Zaki. Parallel graph mining with gpus. In BigMine, pages 1--16, 2014."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.5555\/645496.658027"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2203"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2014.6816705"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2013.6691633"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2818185"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.entcs.2004.12.039"},{"key":"e_1_3_2_1_22_1","first-page":"173","volume-title":"MLG 2006","author":"Nijssen S.","year":"2006","unstructured":"S. Nijssen and J. N. Kok . Frequent subgraph miners: runtimes don't say everything . MLG 2006 , page 173 , 2006 . S. Nijssen and J. N. Kok. Frequent subgraph miners: runtimes don't say everything. MLG 2006, page 173, 2006."},{"key":"e_1_3_2_1_23_1","volume-title":"Mining and Ranking of Generalized Multi-Dimensional Frequent Subgraphs. In IEEE Int. Conf. on Digital Inf. Management (ICDIM)","author":"Petermann A.","year":"2017","unstructured":"A. Petermann Mining and Ranking of Generalized Multi-Dimensional Frequent Subgraphs. In IEEE Int. Conf. on Digital Inf. Management (ICDIM) , 2017 . A. Petermann et al. Mining and Ranking of Generalized Multi-Dimensional Frequent Subgraphs. In IEEE Int. Conf. on Digital Inf. Management (ICDIM), 2017."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0193"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.14778\/2733004.2733034"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2009.133"},{"key":"e_1_3_2_1_27_1","first-page":"1","volume-title":"IEEE Int. Conf. on Field Programmable Logic and Applications (FPL)","author":"Stratikopoulos A.","year":"2014","unstructured":"A. Stratikopoulos : An fpga-based parallel system for frequent subgraph mining . In IEEE Int. Conf. on Field Programmable Logic and Applications (FPL) , pages 1 -- 4 , 2014 . A. Stratikopoulos et al. Hpc-gspan: An fpga-based parallel system for frequent subgraph mining. In IEEE Int. Conf. on Field Programmable Logic and Applications (FPL), pages 1--4, 2014."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2815400.2815410"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1839490.1839491"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-17996-4_15"},{"key":"e_1_3_2_1_31_1","first-page":"392","volume-title":"European Conference on Principles of Data Mining and Knowledge Discovery","author":"W\u00f6rlein M.","year":"2005","unstructured":"M. W\u00f6rlein A quantitative comparison of the subgraph miners mofa, gspan, 'sm, and gaston . In European Conference on Principles of Data Mining and Knowledge Discovery , pages 392 -- 403 . Springer , 2005 . M. W\u00f6rlein et al. A quantitative comparison of the subgraph miners mofa, gspan, 'sm, and gaston. In European Conference on Principles of Data Mining and Knowledge Discovery, pages 392--403. Springer, 2005."},{"key":"e_1_3_2_1_32_1","first-page":"721","volume-title":"IEEE International Conference on Data Mining (ICDM)","author":"Yan X.","year":"2002","unstructured":"X. Yan and J. Han . gspan: Graph-based substructure pattern mining . In IEEE International Conference on Data Mining (ICDM) , pages 721 -- 724 , 2002 . X. Yan and J. Han. gspan: Graph-based substructure pattern mining. In IEEE International Conference on Data Mining (ICDM), pages 721--724, 2002."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956784"},{"key":"e_1_3_2_1_35_1","first-page":"2","volume-title":"Proc. of the 9th USENIX conference on Networked Systems Design and Implementation","author":"Zaharia M.","year":"2012","unstructured":"M. Zaharia Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing . In Proc. of the 9th USENIX conference on Networked Systems Design and Implementation , pages 2 -- 2 , 2012 . M. Zaharia et al. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. In Proc. of the 9th USENIX conference on Networked Systems Design and Implementation, pages 2--2, 2012."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/1367497.1367550"}],"event":{"name":"UCC '17: 10th International Conference on Utility and Cloud Computing","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","IEEE TCSC IEEE Technical Committee on Scalable Computing"],"location":"Austin Texas USA","acronym":"UCC '17"},"container-title":["Proceedings of the Fourth IEEE\/ACM International Conference on Big Data Computing, Applications and Technologies"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3148055.3148064","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3148055.3148064","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:26:33Z","timestamp":1750213593000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3148055.3148064"}},"subtitle":["Transactional Frequent Subgraph Mining with Distributed In-Memory Dataflow Systems"],"short-title":[],"issued":{"date-parts":[[2017,12,5]]},"references-count":35,"alternative-id":["10.1145\/3148055.3148064","10.1145\/3148055"],"URL":"https:\/\/doi.org\/10.1145\/3148055.3148064","relation":{},"subject":[],"published":{"date-parts":[[2017,12,5]]},"assertion":[{"value":"2017-12-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}