{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:51:16Z","timestamp":1781106676406,"version":"3.54.1"},"reference-count":21,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>Subgraph matching, which belongs to NP-hard, faces significant challenges on a large scale graph with billions of nodes, and existing methods are usually confronted with greater challenges from both stability and efficiency. In this article, a subgraph matching method in a distributed system, tree model-based subgraph matching method (TBSGM) is proposed. The authors provide a transformed efficient query tree as a replacement for a query graph. In order to get the tree, they present a cost evaluation model which may help to generate the efficient query tree according to network communication-cost and calculation-cost evaluation. Also, a key set based indexing strategy for intermediate results is given to simplify the matching results during network communication. Extensive experiments with real-world datasets show that TBSGM significantly outperforms other methods in the aspects of scalability and efficiency.<\/jats:p>","DOI":"10.4018\/ijdwm.2018100104","type":"journal-article","created":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T13:08:09Z","timestamp":1537967289000},"page":"67-89","source":"Crossref","is-referenced-by-count":1,"title":["TBSGM"],"prefix":"10.4018","volume":"14","author":[{"given":"Fusheng","family":"Jin","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuliang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Xue","sequence":"additional","affiliation":[{"name":"Northwestern University, Evanston, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Yan","sequence":"additional","affiliation":[{"name":"Technical University of Munich, Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJDWM.2018100104-0","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772696"},{"key":"IJDWM.2018100104-1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.43"},{"key":"IJDWM.2018100104-2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.75"},{"key":"IJDWM.2018100104-3","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2610511"},{"key":"IJDWM.2018100104-4","doi-asserted-by":"publisher","DOI":"10.14778\/2735703.2735705"},{"key":"IJDWM.2018100104-5","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465300"},{"key":"IJDWM.2018100104-6","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-6045-0_4"},{"key":"IJDWM.2018100104-7","first-page":"953","article-title":"Naga: Searching and ranking knowledge.","author":"G.Kasneci","year":"2008","journal-title":"Proceedings of IEEE 24th International Conference on Data Engineering"},{"key":"IJDWM.2018100104-8","doi-asserted-by":"publisher","DOI":"10.14778\/2535568.2448946"},{"key":"IJDWM.2018100104-9","unstructured":"Neo4j. 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