Glossary
- COSI:
-
Cloud-Oriented Subgraph Identification
- DOGMA:
-
Disk-Oriented Graph Matching Algorithm
- RDF:
-
Resource Description Framework
- SPARQL:
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SPARQL Protocol and RDF Query Language
Introduction
Both social network owners and social network users are interested in a variety of queries that involve subgraph matching. In addition, answering SPARQL queries in the Semantic Web’s RDF framework largely involves subgraph matching. For example, the GovTrack dataset (2013) tracks events in the US Congress. In Fig. 1, we see that Jeff Ryster sponsored Bill B0045 whose subject is Health Care. A user who is using such a database might wish to ask queries such as that shown in Fig. 2. This query asks for all amendments (? v1) sponsored by Carla Bunes to bill (? v2) on the subject of health care that were originally sponsored by a male person (? v3). The reader can readily see that when answering this query, we want to...
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References
Abadi DJ, Marcus A, Madden S, Hollenbach KJ (2007) Scalable semantic web data management using vertical partitioning. In: VLDB, Vienna, pp 411–422
Blondel V, Guillaume J, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech Theory Exp 2008:P10008
Borgatti SP, Everett MG, Freeman LC (2002) Ucinet for windows: software for social network analysis. Analytic Technologies, Harvard
Broekstra J, Kampman A, van Harmelen F (2003) Sesame: an architecture for storing and querying RDF data and schema information. In: Fensel D, Hendler JA, Lieberman H, Wahlster W (eds) Spinning the semantic web. MIT Press, Cambridge, pp 197–222
BrĂ¼cheler M, Pugliese A, Subrahmanian VS (2009) DOGMA: a disk-oriented graph matching algorithm for RDF databases. In: ISWC, Chantilly, pp 97–113
BrĂ¼cheler M, Pugliese A, Subrahmanian VS (2010) COSI: cloud oriented subgraph identification in massive social networks. In: Memon N, Alhajj R (eds) ASONAM, Odense. IEEE Computer Society, pp 248–255
BrĂ¼cheler M, Pugliese A, Subrahmanian VS (2011a) Probabilistic subgraph matching on huge social networks. In: Alhajj R, Memon N, Ting I (eds) ASONAM, Kaohsiung. IEEE Computer Society, pp 271–278
BrĂ¼cheler M, Pugliese A, Subrahmanian VS (2011b) A budget-based algorithm for efficient subgraph matching on huge networks. In: Abiteboul S, Bohm K, Koch C, Tan K (eds) ICDE workshop proceedings, Hannover. IEEE Computer Society, pp 94–99
Cheng J, Yu JX, Ding B, Yu PS, Wang H (2008) Fast graph pattern matching. In: ICDE conference, Cancun, pp 913–922
Cheng J, Ke Y, Ng W (2009) Efficient query processing on graph databases. ACM Trans Database Syst 2(1–2):48
Flickr (2013) http://www.flickr.com
Giugno R, Shasha D (2002) Graphgrep: a fast and universal method for querying graphs. In: ICPR conference, Québec City, pp 112–115
Goldman R, McHugh J, Widom J (1999) From semistructured data to XML: migrating the Lore data model and query language. In: Proceedings of the 2nd international workshop on the web and databases (WebDB’99), Philadelphia, pp 25–30
GovTrack dataset (2013) http://www.govtrack.us
Harth A, Decker S (2005) Optimized index structures for querying RDF from the web. In: Proceedings of the 3rd Latin American web congress, Buenos Aires, pp 71–80
Harth A, Umbrich J, Hogan A, Decker S (2007) YARS2: a federated repository for querying graph structured data from the web. In: ISWC, Busan, pp 211–224
Huisman M, Duijn MAV (2005) Software for social network analysis. In: Carrington PJ, Scott J, Wasserman S (eds) Models and methods in social network analysis. Cambridge University Press, Cambridge/New York, pp 270–316
JenaTDB (2013) http://jena.apache.org
Karypis G, Kumar V (1999) A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J Sci Comput 20:359–392
Ke Y, Cheng J, Yu JX (2010) Querying large graph databases. In: DASFAA conference, Tsukuba, pp 487–488
Kiryakov A, Ognyanov D, Manov D (2005) OWLIM – a pragmatic semantic repository for OWL. In: WISE workshops, New York, pp 182–192
Lee C, Park S, Lee D, Lee J, Jeong O, Lee S (2008) A comparison of ontology reasoning systems using query sequences. In: Proceedings of the 2nd international conference on ubiquitous information management and communication, Suwon. ACM, pp 543–546
MahmoudiNasab H, Sakr S (2010) An experimental evaluation of relational RDF storage and querying techniques. In: DASFAA workshops, Tsukuba, pp 215–226
MartĂn MS, Gutierrez C (2009) Representing, querying and transforming social networks with RDF/SPARQL. In: ESWC conference, Heraklion, pp 293–307
Mislove A, Marcon M, Gummadi PK, Druschel P, Bhattacharjee B (2007) Measurement and analysis of online social networks. In: Internet measurement conference, San Diego, pp 29–42
Natale RD, Ferro A, Giugno R, Mongiovì M, Pulvirenti A, Shasha D (2010) SING: subgraph search in non-homogeneous graphs. BMC Bioinform 11:96
Neumann T, Weikum G (2008) RDF-3X: a RISC-style engine for RDF. PVLDB 1(1):647–659
Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45(2):167–256
Nooy W, Mrvar A, Batagelj V (2005) Exploratory social network analysis with Pajek. Structural analysis in the social sciences, vol 27. Cambridge University Press, New York
Pugliese A, Udrea O, Subrahmanian VS (2008) Scaling RDF with time. In: WWW, Beijing, pp 605–614
Ronen R, Shmueli O (2009) Evaluating very large datalog queries on social networks. In: EDBT, Saint-Petersburg, pp 577–587
Sakr S (2009) GraphREL: a decomposition-based and selectivity-aware relational framework for processing sub-graph queries. In: DASFAA conference, Brisbane, pp 123–137
Sesame2 (2013) http://www.openrdf.org
Sintek M, Kiesel M (2006) RDFBroker: a signature-based high-performance RDF store. In: ESWC, Budva, pp 363–377
Stocker M, Seaborne A, Bernstein A, Kiefer C, Reynolds D (2008) SPARQL basic graph pattern optimization using selectivity estimation. In: Proceeding of the 17th international conference on World Wide Web, ACM, Beijing, pp 595–604
The Lehigh University Benchmark (2013) http://swat.cse.lehigh.edu/projects/lubm
Udrea O, Pugliese A, Subrahmanian VS (2007) GRIN: a graph based RDF index. In: AAAI, Vancouver, pp 1465–1470
Wilkinson K, Sayers C, Kuno H, Reynolds D (2003) Efficient RDF storage and retrieval in Jena2. Proc SWDB 3:7–8
Zhang S, Li S, Yang J (2009) GADDI: distance index based subgraph matching in biological networks. In: EDBT conference, Saint-Petersburg, pp 192–203
Zhang S, Li S, Yang J (2010) SUMMA: subgraph matching in massive graphs. In: CIKM conference, Toronto, pp 1285–1288
Zhu K, Zhang Y, Lin X, Zhu G, Wang W (2010) NOVA: a novel and efficient framework for finding subgraph isomorphism mappings in large graphs. In: DASFAA conference, Tsukuba, pp 140–154
Zou L, Chen L, ĂŸzsu MT (2009) Distancejoin: pattern match query in a large graph database. VLDB Conf 2(1):886–897
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BrĂ¼cheler, M., Pugliese, A., Subrahmanian, V.S. (2018). Scaling Subgraph Matching Queries in Huge Networks. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_374
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