DAGMA: Mining directed acyclic graphs

MCCSIS'08 - IADIS Multi Conference on Computer Science and Information Systems; Proceedings of Informatics 2008 and Data Mining 2008

Volumn , Issue , 2008, Pages 11-18

  Werth, T ^a,b   Dreweke, A I ^b   Worlein M ^b   Fischer, I ^b   Philippsen, M ^b  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b UNIVERSITY OF KONSTANZ   (Germany)

Author keywords

Compiler construction; Graph mining

Indexed keywords

COMPUTERS; INFORMATION MANAGEMENT; INFORMATION SYSTEMS; MINERS; MINING; PROGRAM COMPILERS;

ASSEMBLY CODES; CODE SIZE; COMPILER CONSTRUCTION; FLOW GRAPHS; GRAPH MINING; PROGRAM SIZES;

DATA FLOW ANALYSIS;

EID: 58449105135     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Agrawal, R., Imielinski, T., and Swami, A., 1993. Mining association rules between sets of items in large databases. SIGMOD Record, Vol. 22 No. 2. pp. 207-216.
2. Borgelt, C. and Berthold, M., 2002. Mining Molecular Fragments: Finding Relevant Substructures of Molecules. Proc. Int'l Conf. on Data Mining (ICDM'02), Maebashi City, Japan, IEEE Computer Society, pp. 51-58.
3. Chen, Y., Kao, P., and Ko, M., 2004. Mining DAG Patterns from DAG Databases. In Li, Q., Wang, G., and Feng, L. (editors), Proc. 5th Int'l Conf. on Advances in Web-Age Information Management (WAIM'04), Dalian, China, volume 3129 of Lecture Notes in Computer Science, Springer, pp. 579-588.
4. Muntz, C., Nijssen, S., and Kok, J., 2005. Frequent subtree mining - an overview. Fundamenta Informaticae. Vol. 66, No. 1-2, pp. 161-198.
5. Cormen, T. et al., 2001. Introduction to Algorithms, Second Edition. The MIT Press and McGraw-Hill Book Company.
6. Debray, S. et al., 2000. Compiler Techniques for Code Compaction. ACM Transactions on Programming Languages and Systems (TOPLAS), Vol. 22, No. 2, pp. 378-415.
7. Dreweke, A. et al., 2007, Graph-Based Procedural Abstraction. Proc. 5th Int'l Symp. on Code Generation and Optimization (CGO 2007). San Jose, CA, USA, IEEE Computer Society, pp. 259-270.
8. Fortin, S., 1996. The Graph Isomorphism Problem. Technical Report 20, University of Alberta, Edmonton, Alberta, Canada.
9. Guthaus, M. et al., 2001. MiBench: A free, commercially representative embedded benchmark suite. Proc. Int'l Workshop on Workload Characterization (WWC '01), Austin, TX, USA, IEEE Computer Society, pp. 3-14.
10. McKay, B., 1981. Practical Graph Isomorphism. In Congressus Numerantium, Vol. 30, pp. 45-87.
11. Meinl, T. and Fischer, I., 2008. Subgraph mining. In John Wang (editor), Encyclopedia of Data Warehousing and Mining, IGI Global, Hershey, PA, USA, pp. 1059-1063.
12. Termier, A. et al., 2006. Mining Closed Frequent DAGs from Gene Network Data with Dryade. Proc. 20th Conf. of the Japanese Society for Artificial Intelligence, Tokyo, Japan.
13. Werth, T., 2007. Design and Implementation of a DAG Miner. Master's thesis, Friedrich-Alexander University Erlangen-Nuremberg, Germany.
14. Wörlein, M. et al., 2005. A quantitative comparison of the subgraph miners MoFa, gSpan, FFSM, and Gaston. In Jorge, A. et al. (editors), Proc. Conf. on Knowledge Discovery in Database (PKDD'05), Porto, Portugal, volume 3721 of Lecture Notes in Computer Science, Springer, pp. 392-403.
15. Yan, X. and Han, J., 2002. gSpan: Graph-Based Substructure Pattern Mining. Proc. Int'l Conf. on Data Mining (ICDM'02). Maebashi City, Japan, IEEE Computer Society, pp. 721-724.
16. Zaretsky, D. et al., 2006. Dynamic Template Generation for Resource Sharing in Control and Data Flow Graphs. Proc. 19th Int'l Conf. on VLSI Design (VLSI Design 2006). Hyderabad, India, IEEE Computer Society, pp. 465-468.