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Expressive languages for path queries over graph-structured data

Published: 06 June 2010 Publication History

Abstract

For many problems arising in the setting of graph querying (such as finding semantic associations in RDF graphs, exact and approximate pattern matching, sequence alignment, etc.), the power of standard languages such as the widely studied conjunctive regular path queries (CRPQs) is insufficient in at least two ways. First, they cannot output paths and second, more crucially, they cannot express relations among paths.
We thus propose a class of extended CRPQs, called ECRPQs, which add regular relations on tuples of paths, and allow path variables in the heads of queries. We provide several examples of their usefulness in querying graph structured data, and study their properties. We analyze query evaluation and representation of tuples of paths in the output by means of automata. We present a detailed analysis of data and combined complexity of queries, and consider restrictions that lower the complexity of ECRPQs to that of relational conjunctive queries. We study the containment problem, and look at further extensions with first-order features, and with non-regular relations that express arithmetic properties of paths, based on the lengths and numbers of occurrences of labels.

References

[1]
P. A. Abdulla, B. Jonsson, M. Nilsson, M. Saksena. A survey of regular model checking. In CONCUR'04, pages 35--48.
[2]
S. Abiteboul, D. Quass, J. McHugh, J.Widom, J. L. Wiener. The LOREL query language for semistructured data. Int. J. Digit. Libr., 1(1):68--88, 1997.
[3]
S. Abiteboul, P. Buneman, D. Suciu. Data on the web: From relations to semistructured data and XML. Morgan Kauffman, 1999.
[4]
A. V. Aho. Algorithms for finding patterns in strings. In Handbook of TCS, Vol. A, pages 255--300, 1990.
[5]
K. Anyanwu, A. P. Sheth. Á-Queries: enabling querying for semantic associations on the semantic web. In WWW'03, pages 690--699.
[6]
C. L. Barrett, R. Jacob, M. V. Marathe. Formal-language-constrained path problems. SIAM J. Comput., 30(3):809--837, 2000.
[7]
M. Benedikt, L. Libkin, T. Schwentick, L. Segoufin. Definable relations and first-order query languages over strings. JACM, 50(5):694--751, 2003.
[8]
A. Blumensath, E. Gradel. Automatic structures. In LICS'00, pages 51--62.
[9]
V. Bruyere, G. Hansel, C. Michaux, R. Villemaire. Logic and p-recognizable sets of integers. Bull. Belg. Math. Society, 1:191--238, 1994.
[10]
D. Calvanese, G. de Giacomo, M. Lenzerini, M. Y. Vardi. Containment of conjunctive regular path queries with inverse. In KR'00, pages 176--185.
[11]
D. Calvanese, G. de Giacomo, M. Lenzerini, M. Y. Vardi. Rewriting of regular expressions and regular path queries. JCSS, 64(3):443--465, 2002.
[12]
M. Chrobak. Finite automata and unary languages. Theor. Comput. Sci., 47(2):149--158, 1986.
[13]
M. P. Consens, A. O. Mendelzon. GraphLog: a visual formalism for real life recursion. In PODS'90, pages 404--416.
[14]
A. Deutsch, V. Tannen. Optimization properties for classes of conjunctive regular path queries. In DBPL'01, pages 21--39.
[15]
C. Elgot, J. Mezei. On relations defined by generalized finite automata. IBM Journal Research Develop, 9(1):47--68, 1965.
[16]
D. Florescu, A. Levy, D. Suciu. Query containment for conjunctive queries with regular expressions. In PODS'98, pages 139--148.
[17]
D. D. Freydenberger, D. Reidenbach. Bad news on decision problems for patterns. Information and Computation, 208(1):83--96, 2010.
[18]
C. Frougny, J. Sakarovitch. Rational relations with bounded delay. In STACS'91, pages 50--63.
[19]
G. Grahne, A. Thomo. Query answering and containment for regular path queries under distortions. In FoIKS'04, pages 98--115.
[20]
D. Gusfield. Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. Cambridge University Press, 1997.
[21]
D. A. Holland, U. Braun, D. Maclean, K.-K. Muniswamy-Reddy, M. I. Seltzer. Choosing a data model and query language for provenance. In Int. Provenance and Annotation Workshop, 2008.
[22]
O. Ibarra, J. Su, Z. Dang, T. Bultan, R. Kemmerer. Counter machines and verification problems. Theor. Comput. Sci., 289(1):165--189, 2002.
[23]
Y. Kanza, Y. Sagiv. Flexible queries over semistructured data. In PODS'01, pages 40--51.
[24]
K. Kochut, M. Janik. SPARQLeR: Extended SPARQL for semantic association discovery. In ESWC'07, pages 145--159.
[25]
D. Kozen. Lower bounds for natural proof systems. In FOCS'77, pages 254--266.
[26]
W.-J. Lee, L. Raschid, P. Srinivasan, N. Shah, D. L. Rubin, N. F. Noy. Using annotations from controlled vocabularies to find meaningful associations. In Proc. Workshop on Data Integr. in Life Sciences, pages 247--263, 2007.
[27]
J. Lehmann, J. Schuppel, and S. Auer. Discovering unknown connections--the DBpedia relationship finder. In Conf. on Social Semantic Web, pages 99--110, 2007.
[28]
H. W. Lenstra. Integer programming in a fixed number of variables. Math. Oper. Res., 8(4):538--548, 1983.
[29]
A. O. Mendelzon, P. T. Wood. Finding regular simple paths in graph databases. SIAM J. Comput., 24(6):1235--1258, 1995.
[30]
T. Milo, D. Suciu. Index structures for path expressions. In ICDT'99, pages 277--295.
[31]
C. H. Papadimitriou. On the complexity of integer programming. JACM, 28(4):765--768, 1981.
[32]
A. Sheth et al. Semantic association identification and knowledge discovery for national security applications. J. Database Management, 16(1):33--53, 2005.
[33]
A.W. To. Unary finite automata vs. arithmetic progressions. IPL, 109(17):1010--1014, 2009.
[34]
A.W. To. Model checking FO(R) over one-counter processes and beyond. In CSL'09, pages 485--499.
[35]
K. N. Verma, H. Seidl, T. Schwentick. On the complexity of equational Horn clauses. In CADE'05, pages 337--352.
[36]
G. Weikum, G. Kasneci, M. Ramanath, and F. Suchanek. Database and information-retrieval methods for knowledge discovery. Commun. ACM, 52(4):56--64, 2009.

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cover image ACM Conferences
PODS '10: Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
June 2010
350 pages
ISBN:9781450300339
DOI:10.1145/1807085
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 June 2010

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Author Tags

  1. conjunctive queries
  2. graph databases
  3. regular path queries
  4. regular relations

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SIGMOD/PODS '10
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SIGMOD/PODS '10: International Conference on Management of Data
June 6 - 11, 2010
Indiana, Indianapolis, USA

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PODS '10 Paper Acceptance Rate 27 of 113 submissions, 24%;
Overall Acceptance Rate 642 of 2,707 submissions, 24%

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