{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T10:18:49Z","timestamp":1781518729140,"version":"3.54.1"},"reference-count":57,"publisher":"Association for Computing Machinery (ACM)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2017,10]]},"abstract":"<jats:p>\n            RDF is one of the most commonly used knowledge representation forms. Many highly influential knowledge bases, such as Freebase and PubChemRDF, are in RDF format. An RDF data set is usually represented as a collection of\n            <jats:italic>subject-predicate-object<\/jats:italic>\n            triples. Despite the flexibility of RDF triples, it is challenging to serve SPARQL queries on RDF data efficiently by directly managing triples due to the following two reasons. First, heavy joins on a large number of triples are needed for query processing, resulting in a large number of data scans and large redundant intermediate results; Second, weakly-typed triple representation provides suboptimal random access - typically with logarithmic complexity. This data access challenge, unfortunately, cannot be easily met by a better query optimizer as large graph processing is extremely I\/O-intensive. In this paper, we argue that strongly-typed graph representation is the key to high-performance RDF query processing. We propose\n            <jats:bold>Stylus<\/jats:bold>\n            - a strongly-typed store for serving massive RDF data. Stylus exploits a strongly-typed storage scheme to boost the performance of RDF query processing. The storage scheme is essentially a materialized join view on entities, it thus can eliminate a large number of unnecessary joins on triples. Moreover, it is equipped with a compact representation for intermediate results and an efficient graph-decomposition based query planner. Experimental results on both synthetic and real-life RDF data sets confirm that the proposed approach can dramatically boost the performance of SPARQL query processing.\n          <\/jats:p>","DOI":"10.14778\/3149193.3149200","type":"journal-article","created":{"date-parts":[[2017,12,12]],"date-time":"2017-12-12T18:33:38Z","timestamp":1513103618000},"page":"203-216","source":"Crossref","is-referenced-by-count":13,"title":["Stylus"],"prefix":"10.14778","volume":"11","author":[{"given":"Liang","family":"He","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China and Microsoft Research Asia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Shao","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yatao","family":"Li","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanhuan","family":"Xia","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanghua","family":"Xiao","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enhong","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang Jeff","family":"Chen","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2017,10]]},"reference":[{"issue":"1","key":"e_1_2_1_1_1","first-page":"411","article-title":"Scalable semantic web data management using vertical partitioning","volume":"1","author":"Abadi D. J.","year":"2007","unstructured":"D. J. Abadi , A. Marcus , S. R. Madden , and K. Hollenbach . Scalable semantic web data management using vertical partitioning . PVLDB , 1 ( 1 ): 411 -- 422 , 2007 . D. J. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach. Scalable semantic web data management using vertical partitioning. PVLDB, 1(1):411--422, 2007.","journal-title":"PVLDB"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-008-0125-y"},{"key":"e_1_2_1_3_1","volume-title":"The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases. In International Semantic Web Conference","author":"Alexaki S.","year":"2001","unstructured":"S. Alexaki , V. Christophides , G. Karvounarakis , D. Plexousakis , and K. Tolle . The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases. In International Semantic Web Conference , 2001 . S. Alexaki, V. Christophides, G. Karvounarakis, D. Plexousakis, and K. Tolle. The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases. In International Semantic Web Conference, 2001."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-11964-9_13"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732951.2732957"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/11431053_24"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772696"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372099"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2009.07.002"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376746"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/951953.952382"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2463718"},{"key":"e_1_2_1_13_1","volume-title":"Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema","author":"Broekstra J.","year":"2002","unstructured":"J. Broekstra , A. Kampman , and F. V. Harmelen . Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema . 2002 . J. Broekstra, A. Kampman, and F. V. Harmelen. Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema. 2002."},{"key":"e_1_2_1_14_1","volume-title":"EDBT: 18th International Conference on Extending Database Technology","author":"Bursztyn D.","year":"2015","unstructured":"D. Bursztyn , F. Goasdou\u00e9 , and I. Manolescu . Optimizing reformulation-based query answering in RDF . In EDBT: 18th International Conference on Extending Database Technology , 2015 . D. Bursztyn, F. Goasdou\u00e9, and I. Manolescu. Optimizing reformulation-based query answering in RDF. In EDBT: 18th International Conference on Extending Database Technology, 2015."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824093"},{"issue":"1","key":"e_1_2_1_16_1","first-page":"1216","article-title":"An efficient SQL-based RDF querying scheme","volume":"1","author":"Chong E. I.","year":"2005","unstructured":"E. I. Chong , S. Das , G. Eadon , and J. Srinivasan . An efficient SQL-based RDF querying scheme . PVLDB , 1 ( 1 ): 1216 -- 1227 , 2005 . E. I. Chong, S. Das, G. Eadon, and J. Srinivasan. An efficient SQL-based RDF querying scheme. PVLDB, 1(1):1216--1227, 2005.","journal-title":"PVLDB"},{"key":"e_1_2_1_17_1","unstructured":"https:\/\/github.com\/Quetzal-RDF\/quetzal 2017-06-17.  https:\/\/github.com\/Quetzal-RDF\/quetzal 2017-06-17."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989340"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04329-1_21"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.14778\/2078324.2078326"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.5555\/2145432.2145523"},{"key":"e_1_2_1_22_1","unstructured":"https:\/\/github.com\/Caesar11\/gStore 2017-07-31.  https:\/\/github.com\/Caesar11\/gStore 2017-07-31."},{"key":"e_1_2_1_23_1","first-page":"439","volume-title":"EDBT","volume":"14","author":"Gubichev A.","year":"2014","unstructured":"A. Gubichev and T. Neumann . Exploiting the query structure for efficient join ordering in SPARQL queries . In EDBT , volume 14 , pages 439 -- 450 , 2014 . A. Gubichev and T. Neumann. Exploiting the query structure for efficient join ordering in SPARQL queries. In EDBT, volume 14, pages 439--450, 2014."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.websem.2005.06.005"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2610511"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.14778\/2735703.2735705"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2009916.2010019"},{"key":"e_1_2_1_28_1","volume-title":"PSSS","author":"Harris S.","year":"2003","unstructured":"S. Harris and N. Gibbins . 3store: Efficient Bulk RDF Storage . In PSSS , 2003 . S. Harris and N. Gibbins. 3store: Efficient Bulk RDF Storage. In PSSS, 2003."},{"key":"e_1_2_1_29_1","volume-title":"5th International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS2009)","author":"Harris S.","year":"2009","unstructured":"S. Harris , N. Lamb , and N. Shadbolt . 4store: The design and implementation of a clustered RDF store . In 5th International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS2009) , 2009 . S. Harris, N. Lamb, and N. Shadbolt. 4store: The design and implementation of a clustered RDF store. In 5th International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS2009), 2009."},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/LAWEB.2005.25"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30475-3_5"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1526709.1526773"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.14778\/2809974.2809985"},{"key":"e_1_2_1_34_1","unstructured":"http:\/\/lod-cloud.net\/.  http:\/\/lod-cloud.net\/."},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0129626407002843"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.5555\/1082222.1082233"},{"key":"e_1_2_1_37_1","volume-title":"RDFCube: A P2P-Based Three-Dimensional Index for Structural Joins on Distributed Triple Stores","author":"Matono A.","year":"2006","unstructured":"A. Matono , S. M. Pahlevi , and I. Kojima . RDFCube: A P2P-Based Three-Dimensional Index for Structural Joins on Distributed Triple Stores . 2006 . A. Matono, S. M. Pahlevi, and I. Kojima. RDFCube: A P2P-Based Three-Dimensional Index for Structural Joins on Distributed Triple Stores. 2006."},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2011.5767868"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453927"},{"key":"e_1_2_1_40_1","first-page":"310","volume-title":"RDF in MonetDB. In Data Engineering Workshops (ICDEW), 2013 IEEE 29th International Conference on","author":"Pham M.-D.","year":"2013","unstructured":"M.-D. Pham . Self-organizing structured RDF in MonetDB. In Data Engineering Workshops (ICDEW), 2013 IEEE 29th International Conference on , pages 310 -- 313 . IEEE, 2013 . M.-D. Pham. Self-organizing structured RDF in MonetDB. In Data Engineering Workshops (ICDEW), 2013 IEEE 29th International Conference on, pages 310--313. IEEE, 2013."},{"key":"e_1_2_1_41_1","unstructured":"https:\/\/www.w3.org\/TR\/rdf11-concepts\/#section-Graph-Literal.  https:\/\/www.w3.org\/TR\/rdf11-concepts\/#section-Graph-Literal."},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2467799"},{"key":"e_1_2_1_43_1","unstructured":"https:\/\/www.w3.org\/TR\/rdf-sparql-query\/.  https:\/\/www.w3.org\/TR\/rdf-sparql-query\/."},{"key":"e_1_2_1_44_1","unstructured":"https:\/\/github.com\/SoulSight\/Stylus.  https:\/\/github.com\/SoulSight\/Stylus."},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.14778\/2904121.2904123"},{"key":"e_1_2_1_46_1","unstructured":"https:\/\/github.com\/Microsoft\/GraphEngine.  https:\/\/github.com\/Microsoft\/GraphEngine."},{"key":"e_1_2_1_47_1","unstructured":"http:\/\/dsg.uwaterloo.ca\/watdiv\/.  http:\/\/dsg.uwaterloo.ca\/watdiv\/."},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.14778\/1453856.1453965"},{"key":"e_1_2_1_49_1","volume-title":"International Semantic Web Conference","author":"Wilkinson K.","year":"2003","unstructured":"K. Wilkinson , C. Sayers , H. A. Kuno , and D. Reynolds . Efficient RDF Storage and Retrieval in Jena2 . In International Semantic Web Conference , 2003 . K. Wilkinson, C. Sayers, H. A. Kuno, and D. Reynolds. Efficient RDF Storage and Retrieval in Jena2. In International Semantic Web Conference, 2003."},{"key":"e_1_2_1_50_1","volume-title":"XTech 2005 Conference","author":"Wood D.","year":"2005","unstructured":"D. Wood , P. Gearon , and T. Adams . Kowari: A platform for semantic web storage and analysis . In XTech 2005 Conference , 2005 . D. Wood, P. Gearon, and T. Adams. Kowari: A platform for semantic web storage and analysis. In XTech 2005 Conference, 2005."},{"key":"e_1_2_1_51_1","volume-title":"Representation learning of knowledge graphs with entity descriptions","author":"Xie R.","year":"2016","unstructured":"R. Xie , Z. Liu , J. Jia , H. Luan , and M. Sun . Representation learning of knowledge graphs with entity descriptions . 2016 . R. Xie, Z. Liu, J. Jia, H. Luan, and M. Sun. Representation learning of knowledge graphs with entity descriptions. 2016."},{"key":"e_1_2_1_52_1","unstructured":"http:\/\/www.mpi-inf.mpg.de\/departments\/databases-and-information-systems\/research\/yago-naga\/yago\/ 2017.  http:\/\/www.mpi-inf.mpg.de\/departments\/databases-and-information-systems\/research\/yago-naga\/yago\/ 2017."},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806542"},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536349.2536352"},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.14778\/2535570.2488333"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.5555\/1857999.1858071"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.14778\/2002974.2002976"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3149193.3149200","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:32:40Z","timestamp":1672219960000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3149193.3149200"}},"subtitle":["a strongly-typed store for serving massive RDF data"],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":57,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,10]]}},"alternative-id":["10.14778\/3149193.3149200"],"URL":"https:\/\/doi.org\/10.14778\/3149193.3149200","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2017,10]]}}}