NETWORK Procedure

References

  • Adamic, L. A., and Adar, E. (2003). “Friends and Neighbors on the Web.” Social Networks 25:211–230.

  • Aggarwal, C. C., and Wang, H., eds. (2010). Managing and Mining Graph Data. Boston: Springer.

  • Ahuja, R. K., Magnanti, T. L., and Orlin, J. B. (1993). Network Flows: Theory, Algorithms, and Applications. Englewood Cliffs, NJ: Prentice-Hall.

  • AlGhamdi, Z., Jamour, F., Skiadopoulos, S., and Kalnis, P. (2017). “A Benchmark for Betweenness Centrality Approximation Algorithms on Large Graphs.” In SSDBM ’17: Proceedings of the 29th International Conference on Scientific and Statistical Database Management, 1–12. New York: ACM. https://doi.org/10.1145/3085504.3085510.

  • Batagelj, V., and Zaversnik, M. (2003). “An O(m) Algorithm for Cores Decomposition of Networks.” Computing Research Repository cs.DS/0310049.

  • Berlusconi, G., Calderoni, F., Parolini, N., Verani, M., and Piccardi, C. (2016). “Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.” PLoS ONE 11:1–21. https://doi.org/10.1371/journal.pone.0154244.

  • Blondel, V. D., Guillaume, J. L., Lambiotte, R., and Lefebvre, E. (2008). “Fast Unfolding of Communities in Large Networks.” Journal of Statistical Mechanics: Theory and Experiment 10:10000–10014.

  • Boitmanis, K., Freivalds, K., Ledins, P., and Opmanis, R. (2006). “Fast and Simple Approximation of the Diameter and Radius of a Graph.” In Experimental Algorithms, vol. 4007, edited by C. Alvarez and M. Serna, 98–108. Berlin: Springer-Verlag. http://dx.doi.org/10.1007/11764298_9.

  • Bron, C., and Kerbosch, J. (1973). “Algorithm 457: Finding All Cliques of an Undirected Graph.” Communications of the ACM 16:48–50.

  • CNN (2012). “Record Kidney Transplant Chain.” CNN Health. Video. Accessed April 2, 2019. https://www.cnn.com/videos/health/2012/02/20/dnt-kidney-transplant-chain.wls.

  • Conte, D., Foggia, P., Sansone, C., and Vento, M. (2004). “Thirty Years of Graph Matching in Pattern Recognition.” International Journal of Pattern Recognition and Artificial Intelligence 18:265–298.

  • Cormen, T. H., Leiserson, C. E., and Rivest, R. L. (1990). Introduction to Algorithms. Cambridge, MA, and New York: MIT Press and McGraw-Hill.

  • Demetrescu, C. (2010). “9th DIMACS Implementation Challenge—Shortest Paths.” The data are available at http://www.dis.uniroma1.it/challenge9/download.shtml.

  • Dice, L. R. (1945). “Measures of the Amount of Ecologic Association between Species.” Ecology 26:297–302.

  • Fowler, J. H., and Joen, S. (2008). “The Authority of Supreme Court Precedent.” Social Networks 30:16–30. https://doi.org/10.1016/j.socnet.2007.05.001.

  • Gallagher, B. (2006). “Matching Structure and Semantics: A Survey on Graph-Based Pattern Matching.” In AAAI Fall Symposium: Capturing and Using Patterns for Evidence Detection. Menlo Park, CA: Association for the Advancement of Artificial Intelligence.

  • Google (2011). “Google Maps.” Accessed March 16, 2011. http://maps.google.com.

  • Grover, A. (2016). “Node2Vec Reference Implementation.” Accessed January 2021. https://github.com/aditya-grover/node2vec.

  • Grover, A., and Leskovec, J. (2016). “node2vec: Scalable Feature Learning for Networks.” In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 855–864. New York: Association for Computing Machinery. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5108654/.

  • Harley, E. R. (2003). “Graph Algorithms for Assembling Integrated Genome Maps.” Ph.D. diss., University of Toronto.

  • Johnson, D. B. (1975). “Finding All the Elementary Circuits of a Directed Graph.” SIAM Journal on Computing 4:77–84.

  • Kleinberg, J. (1998). “Authoritative Sources in a Hyperlinked Environment.” In Proceedings of the Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 668–677. Philadelphia: SIAM.

  • Krackhardt, D. (1990). “Assessing the Political Landscape: Structure, Cognition, and Power in Organizations.” Administrative Science Quarterly 35:342–369.

  • Krebs, V. (2002). “Uncloaking Terrorist Networks.” First Monday 7. https://firstmonday.org/ojs/index.php/fm/article/view/941/863.

  • Lamensch, M., and Ceci, E. (2018). VAT Fraud: Economic Impact, Challenges and Policy Issues. Technical Report PE 626.076, European Parliament Policy Department for Economic, Scientific and Quality of Life Policies. http://www.europarl.europa.eu/cmsdata/156408/VAT%20Fraud%20Study%20publication.pdf.

  • Lancichinetti, A., and Fortunato, S. (2009). “Community Detection Algorithms: A Comparative Analysis.” Physical Review E 80:056117–056128.

  • Landes, W. M., and Posner, R. A. (1976). “Legal Precedent: A Theoretical and Empirical Analysis.” Journal of Law and Economics 19:249–307.

  • Landrum, G., Tosco, P., Kelley, B., et al. (2022). “RDKit: Open-Source Cheminformatics, Release_2022.03.5.” https://doi.org/10.5281/zenodo.6961488.

  • Langville, A. N., and Meyer, C. D. (2006). Google’s PageRank and Beyond: The Science of Search Engine Rankings. Princeton, NJ: Princeton University Press.

  • Leskovec, J. (2014). “SNAP: Stanford Network Analysis Project.” The data are available at https://snap.stanford.edu/data/index.html.

  • Liu, H., and Wang, J. (2006). “A New Way to Enumerate Cycles in Graph.” In Proceedings of the Advanced International Conference on Telecommunications and International Conference on Internet and Web Applications and Services, 57–59.

  • Mihalcea, R. (2005). “Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-Based Algorithms for Sequence Data Labeling.” In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, 411–418. Vancouver.

  • Needham, M. (2020). “Neo4j Graph Embeddings.” The data are available at https://github.com/neo4j-examples/graph-embeddings.

  • Newman, M. E. J. (2002). “Assortative Mixing in Networks.” Physical Review Letters 89:208701 (1–4).

  • Newman, M. E. J. (2003). “Mixing Patterns in Networks.” Physical Review E 67:026126 (1–13).

  • Newman, M. E. J. (2010). Networks: An Introduction. Oxford: Oxford University Press.

  • Perozzi, B. (2014). “DeepWalk, Version 1.0.2.” Accessed January 2021. https://github.com/phanein/deepwalk.

  • Perozzi, B., Al-Rfou, R., and Skiena, S. (2014). “Deepwalk: Online Learning of Social Representations.” In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 701–710. New York: Association for Computing Machinery. https://doi.org/10.1145/2623330.2623732.

  • Raghavan, U. N., Albert, R., and Kumara, S. (2007). “Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks.” Physical Review E 76:36106–36117.

  • Rochat, Y. (2009). “Closeness Centrality Extended to Unconnected Graphs: The Harmonic Centrality Index.” Paper presented at Sixth Applications of Social Network Analysis Conference, Zurich. https://infoscience.epfl.ch/record/200525/files/%5BEN%5DASNA09.pdf.

  • Ronhovde, P., and Nussinov, Z. (2010). “Local Resolution-Limit-Free Potts Model for Community Detection.” Physical Review E 81:46114–46129.

  • Saltz, M. W. (2013). “A Fast Algorithm for Subgraph Pattern Matching on Large Labeled Graphs.” Master’s thesis, University of Georgia.

  • Shasha, D., Wang, J. T. L., and Giugno, R. (2002). “Algorithmics and Applications of Tree and Graph Searching.” In Proceedings of the Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 39–52. New York: ACM.

  • Sinha, R., and Mihalcea, R. (2007). “Unsupervised Graph-Based Word Sense Disambiguation Using Measures of Word Semantic Similarity.” In Proceedings of the IEEE International Conference on Semantic Computing, 363–369. Los Alamitos, CA: IEEE Computer Society Press.

  • Sleijpen, G. L. G., and van der Vorst, H. A. (2000). “A Jacobi-Davidson Iteration Method for Linear Eigenvalue Problems.” SIAM Review 42:267–293.

  • Sørensen, T. (1948). “A Method of Establishing Groups of Equal Amplitude in Plant Sociology Based on Similarity of Species Content and Its Application to Analyses of the Vegetation on Danish Commons.” Biologiske Skrifter 5:1–34.

  • Sutton, M., Ben-Nun, T., and Barak, A. (2018). “Optimizing Parallel Graph Connectivity Computation via Subgraph Sampling.” In 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 12–21. New York: IEEE. https://doi.org/10.1109/IPDPS.2018.00012.

  • Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., and Mei, Q. (2015). “LINE: Large-Scale Information Network Embedding.” In WWW ’15: Proceedings of the 24th International Conference on World Wide Web, 1067–1077. Geneva: International World Wide Web Conferences Steering Committee.

  • Tarjan, R. E. (1972). “Depth-First Search and Linear Graph Algorithms.” SIAM Journal on Computing 1:146–160.

  • Traag, V. A., Van Dooren, P., and Nesterov, Y. (2011). “Narrow Scope for Resolution-Limit-Free Community Detection.” Physical Review E 84:016114 (1–9). http://dx.doi.org/10.1103/PhysRevE.84.016114.

  • Yen, J. Y. (1971). “Finding the K Shortest Loopless Paths in a Network.” Management Science 17:712–716.

  • Zachary, W. W. (1977). “An Information Flow Model for Conflict and Fission in Small Groups.” Journal of Anthropological Research 33:452–473.

Last updated: August 07, 2026