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2022 | OriginalPaper | Buchkapitel

7. Future Work and Conclusion

verfasst von : Yixiang Fang, Kai Wang, Xuemin Lin, Wenjie Zhang

Erschienen in: Cohesive Subgraph Search Over Large Heterogeneous Information Networks

Verlag: Springer International Publishing

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Abstract

Although much research effort has been devoted to CSS over large HINs over the past several decades, there are still many issues that are not well addressed, thus there is still much room to perform further study on CSS over large HINs in the future, from the perspectives of effective CSMs, computational efficiency, parameter optimization, tools, etc. In this chapter, we discuss several important future research directions about CSS over HINs, including novel application-driven CSMs, efficient search algorithms, parameter optimization, and an online repository for collecting HIN datasets, tools, and algorithm codes, which can provide researchers some good starting points to work in this area. In addition, we draw a brief conclusion for the book.

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Literatur
10.
Zurück zum Zitat Bahmani, B., Kumar, R., & Vassilvitskii, S. (2012). Densest subgraph in streaming and mapreduce. PVLDB, 5(5), 454–465. Bahmani, B., Kumar, R., & Vassilvitskii, S. (2012). Densest subgraph in streaming and mapreduce. PVLDB, 5(5), 454–465.
24.
Zurück zum Zitat Chan, T. H., Sozio, M., & Sun, B. (2019). Distributed approximate k-core decomposition and min-max edge orientation: Breaking the diameter barrier. In IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 345–354). IEEE. Chan, T. H., Sozio, M., & Sun, B. (2019). Distributed approximate k-core decomposition and min-max edge orientation: Breaking the diameter barrier. In IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 345–354). IEEE.
27.
Zurück zum Zitat Charikar, M. (2000). Greedy approximation algorithms for finding dense components in a graph. In International Workshop on Approximation Algorithms for Combinatorial Optimization (pp. 84–95). Springer. Charikar, M. (2000). Greedy approximation algorithms for finding dense components in a graph. In International Workshop on Approximation Algorithms for Combinatorial Optimization (pp. 84–95). Springer.
28.
Zurück zum Zitat Chatterjee, A., Nardi, C., Oberije, C., & Lambin, P. (2021). Knowledge graphs for covid-19: An exploratory review of the current landscape. Journal of Personalized Medicine, 11(4), 300.CrossRef Chatterjee, A., Nardi, C., Oberije, C., & Lambin, P. (2021). Knowledge graphs for covid-19: An exploratory review of the current landscape. Journal of Personalized Medicine, 11(4), 300.CrossRef
40.
Zurück zum Zitat Chu, D., Zhang, F., Lin, X., Zhang, W., Zhang, Y., Xia, Y., & Zhang, C. (2020). Finding the best k in core decomposition: A time and space optimal solution. In ICDE (pp. 685–696). IEEE. Chu, D., Zhang, F., Lin, X., Zhang, W., Zhang, Y., Xia, Y., & Zhang, C. (2020). Finding the best k in core decomposition: A time and space optimal solution. In ICDE (pp. 685–696). IEEE.
46.
Zurück zum Zitat Dasari, N. S., Desh, R., & Zubair, M. (2014). Park: An efficient algorithm for k-core decomposition on multicore processors. In IEEE International Conference on Big Data (Big Data) (pp. 9–16). IEEE. Dasari, N. S., Desh, R., & Zubair, M. (2014). Park: An efficient algorithm for k-core decomposition on multicore processors. In IEEE International Conference on Big Data (Big Data) (pp. 9–16). IEEE.
53.
Zurück zum Zitat Esfandiari, H., Lattanzi, S., & Mirrokni, V. (2018). Parallel and streaming algorithms for k-core decomposition. arXiv preprint arXiv:1808.02546. Esfandiari, H., Lattanzi, S., & Mirrokni, V. (2018). Parallel and streaming algorithms for k-core decomposition. arXiv preprint arXiv:1808.02546.
62.
Zurück zum Zitat Fang, Y., Yang, Y., Zhang, W., Lin, X., & Cao, X. (2020). Effective and efficient community search over large heterogeneous information networks. PVLDB, 13(6), 854–867. Fang, Y., Yang, Y., Zhang, W., Lin, X., & Cao, X. (2020). Effective and efficient community search over large heterogeneous information networks. PVLDB, 13(6), 854–867.
63.
Zurück zum Zitat Fang, Y., Yu, K., Cheng, R., Lakshmanan, L. V., & Lin, X. (2019). Efficient algorithms for densest subgraph discovery. PVLDB, 12(11), 1719–1732. Fang, Y., Yu, K., Cheng, R., Lakshmanan, L. V., & Lin, X. (2019). Efficient algorithms for densest subgraph discovery. PVLDB, 12(11), 1719–1732.
73.
Zurück zum Zitat Goldberg, A. V. (1984). Finding a maximum density subgraph. University of California Berkeley, CA. Goldberg, A. V. (1984). Finding a maximum density subgraph. University of California Berkeley, CA.
90.
Zurück zum Zitat Jakma, P., Orczyk, M., Perkins, C. S., & Fayed, M. (2012). Distributed k-core decomposition of dynamic graphs. In Proceedings of the 2012 ACM Conference on CoNEXT Student Workshop (pp. 39–40). Jakma, P., Orczyk, M., Perkins, C. S., & Fayed, M. (2012). Distributed k-core decomposition of dynamic graphs. In Proceedings of the 2012 ACM Conference on CoNEXT Student Workshop (pp. 39–40).
93.
Zurück zum Zitat Kabir, H., & Madduri, K. (2017). Parallel k-core decomposition on multicore platforms. In IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 1482–1491). IEEE. Kabir, H., & Madduri, K. (2017). Parallel k-core decomposition on multicore platforms. In IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 1482–1491). IEEE.
94.
Zurück zum Zitat Kannan, R., & Vinay, V. (1999). Analyzing the structure of large graphs. Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn. Kannan, R., & Vinay, V. (1999). Analyzing the structure of large graphs. Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn.
96.
Zurück zum Zitat Khuller, S., & Saha, B. (2009). On finding dense subgraphs. In International Colloquium on Automata, Languages, and Programming (pp. 597–608). Springer. Khuller, S., & Saha, B. (2009). On finding dense subgraphs. In International Colloquium on Automata, Languages, and Programming (pp. 597–608). Springer.
107.
Zurück zum Zitat Li, R.-H., Qin, L., Yu, J. X., & Mao, R. (2017). Finding influential communities in massive networks. The VLDB Journal, 26(6), 751–776.CrossRef Li, R.-H., Qin, L., Yu, J. X., & Mao, R. (2017). Finding influential communities in massive networks. The VLDB Journal, 26(6), 751–776.CrossRef
124.
Zurück zum Zitat Ma, C., Fang, Y., Cheng, R., Lakshmanan, L. V., Zhang, W., & Lin, X. (2020). Efficient algorithms for densest subgraph discovery on large directed graphs. In SIGMOD (pp. 1051–1066). ACM. Ma, C., Fang, Y., Cheng, R., Lakshmanan, L. V., Zhang, W., & Lin, X. (2020). Efficient algorithms for densest subgraph discovery on large directed graphs. In SIGMOD (pp. 1051–1066). ACM.
131.
Zurück zum Zitat Mitzenmacher, M., Pachocki, J., Peng, R., Tsourakakis, C., & Xu, S. C. (2015). Scalable large near-clique detection in large-scale networks via sampling. In SIGKDD (pp. 815–824). ACM. Mitzenmacher, M., Pachocki, J., Peng, R., Tsourakakis, C., & Xu, S. C. (2015). Scalable large near-clique detection in large-scale networks via sampling. In SIGKDD (pp. 815–824). ACM.
132.
Zurück zum Zitat Montresor, A., De Pellegrini, F., & Miorandi, D. (2012). Distributed k-core decomposition. IEEE TPDS, 24(2), 288–300. Montresor, A., De Pellegrini, F., & Miorandi, D. (2012). Distributed k-core decomposition. IEEE TPDS, 24(2), 288–300.
162.
Zurück zum Zitat Tsourakakis, C. (2015). The k-clique densest subgraph problem. In WWW (pp. 1122–1132). Tsourakakis, C. (2015). The k-clique densest subgraph problem. In WWW (pp. 1122–1132).
176.
Zurück zum Zitat Weng, T., Zhou, X., Li, K., Peng, P., & Li, K. (2022). Efficient distributed approaches to core maintenance on large dynamic graphs. IEEE Trans. Parallel Distributed System, 33(1), 129–143.CrossRef Weng, T., Zhou, X., Li, K., Peng, P., & Li, K. (2022). Efficient distributed approaches to core maintenance on large dynamic graphs. IEEE Trans. Parallel Distributed System, 33(1), 129–143.CrossRef
Metadaten
Titel
Future Work and Conclusion
verfasst von
Yixiang Fang
Kai Wang
Xuemin Lin
Wenjie Zhang
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-030-97568-5_7

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