Abstract
Heterogeneous information network (HIN) provides a new paradigm to manage networked data. Meanwhile, it also introduces new challenges for many data mining tasks. Here, we give a brief survey on recent developments of this field. Concretely, we have analyzed more than 100 referred papers published in the referred conferences and journals in recent years and divided them into seven categories according to their data mining tasks. In this chapter, we will summarize the developments on these seven main data mining tasks. Moreover, these data mining tasks are coarsely ordered from basic task to advanced task.
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References
Aggarwal, C., Xie, Y., Yu, P.: Towards community detection in locally heterogeneous networks. In: SDM, pp. 391–402 (2011)
Aggarwal, C.C., Xie, Y., Yu, P.S.: On dynamic link inference in heterogeneous networks. In: SDM, pp. 415–426 (2012)
Aggarwal, C.C., Xie, Y., Yu, P.S.: A framework for dynamic link prediction in heterogeneous networks. Stat. Anal. Data Min. ASA Data Sci. J. 7(1), 14–33 (2014)
Alqadah, F., Bhatnagar, R.: A game theoretic framework for heterogeneous information network clustering. In: KDD, pp. 795–802 (2011)
Angelova, R., Kasneci, G., Weikum, G.: Graffiti: graph-based classification in heterogeneous networks. In: WWW, pp. 139–170 (2012)
Bangcharoensap, P., Murata, T., Kobayashi, H., Shimizu, N.: Transductive classification on heterogeneous information networks with edge betweenness-based normalization. In: WSDM, pp. 437–446 (2016)
Boden, B., Ester, M., Seidl, T.: Density-based subspace clustering in heterogeneous networks. In: ECML/PKDD, pp. 149–164 (2014)
Bu, S., Hong, X., Peng, Z., Li, Q.: Integrating meta-path selection with user-preference for top-k relevant search in heterogeneous information networks. In: CSCWD, pp. 301–306 (2014)
Burke, R., Vahedian, F., Mobasher, B.: Hybrid recommendation in heterogeneous networks. In: UMAP, pp. 49–60 (2014)
Cao, B., Kong, X., Yu, P.S.: Collective prediction of multiple types of links in heterogeneous information networks. In: ICDM, pp. 50–59 (2014)
Chen, J., Gao, H., Wu, Z., Li, D.: Tag co-occurrence relationship prediction in heterogeneous information networks. In: ICPADS, pp. 528–533 (2013)
Chen, J., Dai, W., Sun, Y., Dy, J.: Clustering and ranking in heterogeneous information networks via gamma-poisson model. In: SDM, pp. 425–432 (2015)
Chen, S.D., Chen, Y.Y., Han, J., Moulin, P.: A feature-enhanced ranking-based classifier for multimodal data and heterogeneous information networks. In: ICDM, pp. 997–1002 (2013)
Cruz, J.D., Bothorel, C., Poulet, F.: Integrating heterogeneous information within a social network for detecting communities. In: ASONAM, pp. 1453–1454 (2013)
Deng, H., Lyu, M.R., King, I.: A generalized Co-HITS algorithm and its application to bipartite graphs. In: KDD, pp. 239–248 (2009)
Deng, H., Zhao, B., Han, J.: Collective topic modeling for heterogeneous networks. In: SIGIR, pp. 1109–1110 (2011)
Deng, H., Han, J., Zhao, B., Yu, Y., Lin, C.X.: Probabilistic topic models with biased propagation on heterogeneous information networks. In: KDD, pp. 795–802 (2011)
Doan, A., Madhavan, J., Domingos, P., Halevy, A.: Ontology matching: a machine learning approach. Handbook on Ontologies, pp. 385–403. Springer, Berlin (2004)
Dong, Y., Tang, J., Wu, S., Tian, J., Chawla, N.V., Rao, J., Cao, H.: Link prediction and recommendation across heterogeneous social networks. In: ICDM, pp. 181–190 (2012)
Fang, Y., Lin, W., Zheng, V.W., Wu, M., Chang, C.C., Li, X.L.: Semantic proximity search on graphs with metagraph-based learning. In: ICDE, pp. 277–288 (2016)
Gupta, M., Gao, J., Han, J.: Community distribution outlier detection in heterogeneous information networks. In: ECML, pp. 557–573 (2013)
Gupta, M., Gao, J., Yan, X., Cam, H., Han, J.: On detecting association-based clique outliers in heterogeneous information networks. In: ASONAM, pp. 108–115 (2013)
He, J., Bailey, J., Zhang, R.: Exploiting transitive similarity and temporal dynamics for similarity search in heterogeneous information networks. In: International Conference on Database Systems for Advanced Applications, pp. 141–155 (2014)
Hou U.L., Yao, K., Mak, H.: PathSimExt: revisiting PathSim in heterogeneous information networks. In: WAIM, pp. 38–42 (2014)
Hu, Q., Xie, S., Zhang, J., Zhu, Q., Guo, S., Yu, P.S.: HeteroSales: utilizing heterogeneous social networks to identify the next enterprise customer. In: WWW, pp. 41–50 (2016)
Huang, H., Zubiaga, A., Ji, H., Deng, H., Wang, D., Le, H.K., Abdelzaher, T.F., Han, J., Leung, A., Hancock, J.P., Others: Tweet ranking based on heterogeneous networks. In: COLING, pp. 1239–1256 (2012)
Huang, J., Nie, F., Huang, H., Tu, Y.C.: Trust prediction via aggregating heterogeneous social networks. In: CIKM, pp. 1774–1778 (2012)
Huang, Z., Zheng, Y., Cheng, R., Sun, Y., Mamoulis, N., Li, X.: Meta structure: computing relevance in large heterogeneous information networks. In: SIGKDD, pp. 1595–1604 (2016)
Jacob, Y., Denoyer, L., Gallinari, P.: Learning latent representations of nodes for classifying in heterogeneous social networks. In: WSDM, pp. 373–382 (2014)
Jain, A.K.: Data clustering: 50 years beyond K-means. Pattern Recognit. Lett. 31(8), 651–666 (2010)
Jamali, M., Lakshmanan, L.: HeteroMF: recommendation in heterogeneous information networks using context dependent factor models. In: WWW, pp. 643–654 (2013)
Jeh, G., Widom, J.: SimRank: a measure of structural-context similarity. In: KDD, pp. 538–543 (2002)
Jeh, G., Widom, J.: Scaling personalized web search. In: WWW, pp. 271–279 (2003)
Jendoubi, S., Martin, A., Lietard, L., Yaghlane, B.B.: Classification of message spreading in a heterogeneous social network. In: IPMU, pp. 66–75 (2014)
Ji, M., Sun, Y., Danilevsky, M., Han, J., Gao, J.: Graph regularized transductive classification on heterogeneous information networks. In: ECML/PKDD, pp. 570–586 (2010)
Ji, M., Han, J., Danilevsky, M.: Ranking-based classification of heterogeneous information networks. In: KDD, pp. 1298–1306 (2011)
Jin, S., Zhang, J., Yu, P.S., Yang, S., Li, A.: Synergistic partitioning in multiple large scale social networks. In: IEEE BigData, pp. 281–290 (2014)
Klau, G.W.: A new graph-based method for pairwise global network alignment. BMC Bioinform. 10(Suppl 1), S59 (2009)
Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. In: SODA, pp. 668–677 (1999)
Kong, X., Yu, P.S., Ding, Y., Wild, D.J.: Meta path-based collective classification in heterogeneous information networks. In: CIKM, pp. 1567–1571 (2012)
Kong, X., Cao, B., Yu, P.S.: Multi-label classification by mining label and instance correlations from heterogeneous information networks. In: KDD, pp. 614–622 (2013)
Kong, X., Zhang, J., Yu, P.S.: Inferring anchor links across multiple heterogeneous social networks. In: CIKM, pp. 179–188 (2013)
Koutra, D., Tong, H., Lubensky, D.: Big-align: fast bipartite graph alignment. In: ICDM, pp. 389–398 (2013)
Kuck, J., Zhuang, H., Yan, X., Cam, H., Han, J.: Query-based outlier detection in heterogeneous information networks. In: EDBT, pp. 325–336 (2015)
Lafferty, J., McCallum, A., Pereira, F.C.N.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: ICML, pp. 282–289 (2001)
Lao, N., Cohen, W.: Fast query execution for retrieval models based on path constrained random walks. In: KDD, pp. 881–888 (2010)
Lao, N., Cohen, W.W.: Relational retrieval using a combination of path-constrained random walks. Mach. Learn. 81(2), 53–67 (2010)
Li, C., Sun, J., Xiong, Y., Zheng, G.: An efficient drug-target interaction mining algorithm in heterogeneous biological networks. In: PAKDD, pp. 65–76 (2014)
Li, X., Ng, M.K., Ye, Y.: HAR: hub, authority and relevance scores in multi-relational data for query search. In: SDM, pp. 141–152 (2012)
Li, Y., Shi, C., Yu, P.S., Chen, Q.: HRank: a path based ranking method in heterogeneous information network. In: WAIM, pp. 553–565 (2014)
Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. J. Am. Soc. Inf. Sci. Tech. 58(7), 1019–1031 (2007)
Liu, F., Xia, S.: Link prediction in aligned heterogeneous networks. In: PAKDD, pp. 33–44 (2015)
Liu, L., Tang, J., Han, J., Yang, S.: Learning influence from heterogeneous social networks. Data Min. Knowl. Discov. 25(3), 511–544 (2012)
Liu, X., Yu, Y., Guo, C., Sun, Y.: Meta-path-based ranking with pseudo relevance feedback on heterogeneous graph for citation recommendation. In: CIKM, pp. 121–130 (2014)
Lu, C.T., Xie, S., Shao, W., He, L., Yu, P.S.: Item recommendation for emerging online businesses. In: IJCAI, pp. 3797–3803 (2016)
Luo, C., Guan, R., Wang, Z., Lin, C.: HetPathMine: a novel transductive classification algorithm on heterogeneous information networks. In: Advances in Information Retrieval, vol. 8416, pp. 210–221 (2014)
Luo, C., Pang, W., Wang, Z.: Hete-CF: social-based collaborative filtering recommendation using heterogeneous relations. In: ICDM, pp. 917–922 (2014)
Luo, C., Pang, W., Wang, Z.: Semi-supervised clustering on heterogeneous information networks. In: Advances in Knowledge Discovery and Data Mining, vol. 8444, pp. 548–559 (2014)
Ma, H., King, I., Lyu, M.R.: Learning to recommend with social trust ensemble. In: SIGIR, pp. 203–210 (2009)
Ma, Y., Yang, N., Li, C., Zhang, L., Yu, P.S.: Predicting neighbor distribution in heterogeneous information networks. In: SDM, pp. 784–791 (2015)
Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: a versatile graph matching algorithm and its application to schema matching. In: ICDE, pp. 117–128 (2002)
Meng, X., Shi, C., Li, Y., Zhang, L., Wu, B.: Relevance measure in large-scale heterogeneous networks. In: APWeb, pp. 636–643 (2014)
Newman, M.E.J., Girvan, M., M.E.J., Newman, M.G.: Finding and evaluating community structure in networks. Phys. Rev. E 69(026113), 1757–1771 (2004)
Ng, M.K., Li, X., Ye, Y., Ng, M., Li, X., Ye, Y.: MultiRank: co-ranking for objects and relations in multi-relational data. In: KDD, pp. 1217–1225 (2011)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. In: Stanford InfoLab, pp. 1–14 (1998)
Popescul, A., Ungar, L.H.: Statistical relational learning for link prediction. In: IJCAI Workshop on Learning Statistical Models from Relational Data, vol. 2003 (2003)
Qi, G.J., Aggarwal, C.C., Huang, T.S.: On clustering heterogeneous social media objects with outlier links. In: WSDM, pp. 553–562 (2012)
Qiu, C., Chen, W., Wang, T., Lei, K.: Overlapping community detection in directed heterogeneous social network. In: WAIM, pp. 490–493 (2015)
Ren, X., Liu, J., Yu, X., Khandelwal, U., Gu, Q., Wang, L., Han, J.: ClusCite: effective citation recommendation by information network-based clustering. In: KDD, pp. 821–830 (2014)
Rossi, R.G., de Paulo Faleiros, T., de Andrade Lopes, A., Rezende, S.O.: Inductive model generation for text categorization using a bipartite heterogeneous network. In: ICDM, pp. 1086–1091 (2012)
Sales-Pardo, M., Guimera, R., Moreira, A.A., Amaral, L.A.N.: Extracting the hierarchical organization of complex systems. Proc. Natl. Acad. Sci. 104(39), 15224–15229 (2007)
Shi, C., Kong, X., Yu, P.S., Xie, S., Wu, B.: Relevance search in heterogeneous networks. In: EDBT, pp. 180–191 (2012)
Shi, C., Zhou, C., Kong, X., Yu, P.S., Liu, G., Wang, B.: HeteRecom: a semantic-based recommendation system in heterogeneous networks. In: KDD, pp. 1552–1555 (2012)
Shi, C., Kong, X., Huang, Y., Philip, S.Y., Wu, B.: Hetesim: a general framework for relevance measure in heterogeneous networks. IEEE Trans. Knowl. Data Eng. 26(10), 2479–2492 (2014)
Shi, C., Wang, R., Li, Y., Yu, P.S., Wu, B.: Ranking-based clustering on general heterogeneous information networks by network projection. In: CIKM, pp. 699–708 (2014)
Shi, C., Zhang, Z., Luo, P., Yu, P.S., Yue, Y., Wu, B.: Semantic path based personalized recommendation on weighted heterogeneous information networks. In: CIKM, pp. 453–462 (2015)
Shi, C., Li, Y., Philip, S.Y., Wu, B.: Constrained-meta-path-based ranking in heterogeneous information network. Knowl. Inf. Syst. 1–29 (2016)
Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888–905 (2000)
Shih, Y.K., Parthasarathy, S.: Scalable global alignment for multiple biological networks. BMC Bioinf. 13, 1–13 (2012)
Soulier, L., Jabeur, L.B., Tamine, L., Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model. J. Am. Soc. Inf. Sci. Technol. 64(3), 500–515 (2013)
Srebro, N., Jaakkola, T.: Weighted low-rank approximations. In: ICML, pp. 720–727 (2003)
Sun, Y., Yu, Y., Han, J.: Ranking-based clustering of heterogeneous information networks with star network schema. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 797–806 (2009)
Sun, Y., Han, J., Zhao, P., Yin, Z., Cheng, H., Wu, T.: RankClus: integrating clustering with ranking for heterogeneous information network analysis. In: EDBT, pp. 565–576 (2009)
Sun, Y., Barber, R., Gupta, M., Aggarwal, C.C., Han, J.: Co-author relationship prediction in heterogeneous bibliographic networks. In: ASONAM, pp. 121–128 (2011)
Sun, Y., Aggarwal, C., Han, J.: Relation strength-aware clustering of heterogeneous information networks with incomplete attributes. In: VLDB, pp. 394–405 (2012)
Sun, Y., Han, J., Aggarwal, C.C., Chawla, N.V.: When will it happen?: relationship prediction in heterogeneous information networks. In: WSDM, pp. 663–672 (2012)
Sun, Y., Norick, B., Han, J., Yan, X., Yu, P.S., Yu, X.: Integrating meta-path selection with user-guided object clustering in heterogeneous information networks. In: KDD, pp. 1348–1356 (2012)
Sun, Y.Z., Han, J.W., Yan, X.F., Yu, P.S., Wu, T.: PathSim: meta path-based Top-K similarity search in heterogeneous information networks. In: VLDB, pp. 992–1003 (2011)
Tang, J., Qu, M., Mei, Q.: PTE: predictive text embedding through large-scale heterogeneous text networks. In: KDD, pp. 1165–1174 (2015)
Tang, J., Lou, T., Kleinberg, J., Wu, S.: Transfer learning to infer social ties across heterogeneous networks. ACM Trans. Inf. Syst. 34(2), 7:1–7:43 (2016)
Tsai, M.H., Aggarwal, C., Huang, T.: Ranking in heterogeneous social media. In: WSDM, pp. 613–622 (2014)
Umeyama, S.: An eigendecomposition approach to weighted graph matching problems. IEEE Trans. Pattern Anal. Mach. Intell. 10(5), 695–703 (1988)
Wakita, K., Tsurumi, T.: Finding community structure in mega-scale social networks. In: WWW, pp. 1275–1276 (2007)
Wan, M., Ouyang, Y., Kaplan, L., Han, J.: Graph regularized meta-path based transductive regression in heterogeneous information network. In: SDM, pp. 918–926 (2015)
Wang, B., Tang, J., Fan, W., Chen, S., Tan, C., Yang, Z.: Query-dependent cross-domain ranking in heterogeneous network. Knowl. Inf. Syst. 34(1), 109–145 (2013)
Wang, C., Raina, R., Fong, D., Zhou, D., Han, J., Badros, G.J.: Learning relevance from heterogeneous social network and its application in online targeting. In: SIGIR, pp. 655–664 (2011)
Wang, C., Danilevsky, M., Liu, J., Desai, N., Ji, H., Han, J.: Constructing topical hierarchies in heterogeneous information networks. In: ICDM, pp. 767–776 (2013)
Wang, C., Song, Y., El-Kishky, A., Roth, D., Zhang, M., Han, J.: Incorporating world knowledge to document clustering via heterogeneous information networks. In: KDD, pp. 1215–1224 (2015)
Wang, C., Song, Y., Li, H., Zhang, M., Han, J.: Knowsim: a document similarity measure on structured heterogeneous information networks. In: ICDM, pp. 1015–1020 (2015)
Wang, C., Song, Y., Li, H., Zhang, M., Han, J.: Text classification with heterogeneous information network kernels. In: AAAI, pp. 2130–2136 (2016)
Wang, C., Sun, Y., Song, Y., Han, J., Song, Y., Wang, L., Zhang, M.: Relsim: relation similarity search in schema-rich heterogeneous information networks. In: Siam International Conference on Data Mining, pp. 621–629 (2016)
Wang, G., Hu, Q., Yu, P.S.: Influence and similarity on heterogeneous networks. In: CIKM, pp. 1462–1466 (2012)
Wang, Q., Peng, Z., Jiang, F., Li, Q.: LSA-PTM: a propagation-based topic model using latent semantic analysis on heterogeneous information networks. In: WAIM, pp. 13–24 (2013)
Wang, Q., Peng, Z., Wang, S., Yu, P.S., Li, Q., Hong, X.: cluTM: content and link integrated topic model on heterogeneous information networks. In: WAIM, pp. 207–218 (2015)
Wang, R., Shi, C., Yu, P.S., Wu, B.: Integrating clustering and ranking on hybrid heterogeneous information network. In: PAKDD, pp. 583–594 (2013)
Wang, S., Xie, S., Zhang, X., Li, Z., Yu, P.S., Shu, X.: Future influence ranking of scientific literature. In: SDM, pp. 749–757 (2014)
Wu, J., Chen, L., Yu, Q., Han, P., Wu, Z.: Trust-aware media recommendation in heterogeneous social networks. WWW 18(1), 139–157 (2015)
Xiong, Y., Zhu, Y., Yu, P.S.: Top-k similarity join in heterogeneous information networks. IEEE Trans. Knowl. Data Eng. 27(6), 1710–1723 (2015)
Yang, C., Sun, J., Ma, J., Zhang, S., Wang, G., Hua, Z.: Scientific collaborator recommendation in heterogeneous bibliographic networks. In: HICSS, pp. 552–561 (2015)
Yang, T., Jin, R., Chi, Y., Zhu, S.: Combining link and content for community detection: a discriminative approach. In: KDD, pp. 927–936 (2009)
Yang, X., Steck, H., Liu, Y.: Circle-based recommendation in online social networks. In: KDD, pp. 1267–1275 (2012)
Yang, Y., Chawla, N.V., Sun, Y., Han, J.: Predicting links in multi-relational and heterogeneous networks. In: ICDM, pp. 755–764 (2012)
Yang, Y., Tang, J., Keomany, J., Zhao, Y., Li, J., Ding, Y., Li, T., Wang, L.: Mining competitive relationships by learning across heterogeneous networks. In: CIKM, pp. 1432–1441 (2012)
Yu, P.S., Zhang, J.: MCD: mutual clustering across multiple social networks. In: IEEE International Congress on Big Data, pp. 762–771 (2015)
Yu, X., Gu, Q., Zhou, M., Han, J.: Citation prediction in heterogeneous bibliographic networks. In: SDM, pp. 1119–1130 (2012)
Yu, X., Sun, Y., Norick, B., Mao, T., Han, J.: User guided entity similarity search using meta-path selection in heterogeneous information networks. In: CIKM, pp. 2025–2029 (2012)
Yu, X., Ren, X., Sun, Y., Sturt, B., Khandelwal, U., Gu, Q., Norick, B., Han, J.: Recommendation in heterogeneous information networks with implicit user feedback. In: RecSys, pp. 347–350 (2013)
Yu, X., Ren, X., Sun, Y., Gu, Q., Sturt, B., Khandelwal, U., Norick, B., Han, J.: Personalized entity recommendation: a heterogeneous information network approach. In: WSDM, pp. 283–292 (2014)
Zhan, Q., Zhang, J., Wang, S., Yu, P.S., Xie, J.: Influence maximization across partially aligned heterogeneous social networks. In: PAKDD, pp. 58–69 (2015)
Zhan, Q., Zhang, J., Philip, S.Y., Emery, S., Xie, J.: Discover tipping users for cross network influencing. In: 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI), pp. 67–76 (2016)
Zhang, A., Xie, X., Chang, K.C.C., Gunter, C.A., Han, J., Wang, X.: Privacy risk in anonymized heterogeneous information networks. In: EDBT, pp. 595–606 (2014)
Zhang, J., Yu, P.: Community detection for emerging networks. In: SDM, pp. 127–135 (2015)
Zhang, J., Yu, P.S.: Integrated anchor and social link predictions across social networks. In: IJCAI, pp. 2125–2131 (2015)
Zhang, J., Yu, P.S.: Multiple anonymized social networks alignment. In: ICDM, pp. 599–608 (2015)
Zhang, J., Yu, P.S.: PCT: partial co-alignment of social networks. In: WWW, pp. 749–759 (2016)
Zhang, J., Kong, X., Yu, P.S.: Predicting social links for new users across aligned heterogeneous social networks. In: ICDM, pp. 1289–1294 (2013)
Zhang, J., Yu, P.S., Zhou, Z.H.: Meta-path based multi-network collective link prediction. In: KDD, pp. 1286–1295 (2014)
Zhang, J., Kong, X., Yu, P.S.: Transferring heterogeneous links across location-based social networks. In: WSDM, pp. 303–312 (2014)
Zhang, J., Kong, X., Jie, L., Chang, Y., Yu, P.S.: NCR: a scalable network-based approach to co-ranking in question-and-answer sites. In: CIKM, pp. 709–718 (2014)
Zhang, J., Yu, P.S., Lv, Y.: Organizational chart inference. In: KDD, pp. 1435–1444 (2015)
Zhang, J., Shao, W., Wang, S., Kong, X., Yu, P.S.: Partial network alignment with anchor meta path and truncated generic stable matching. ArXiv e-prints (2015)
Zhang, J., Yu, P.S., Lv, Y., Zhan, Q.: Information diffusion at workplace. In: CIKM, pp. 1673–1682. ACM (2016)
Zhang, M., Hu, H., He, Z., Wang, W.: Top-k similarity search in heterogeneous information networks with x-star network schema. Expert Syst. Appl. 42(2), 699–712 (2015)
Zhang, Y., Tang, J., Yang, Z., Pei, J., Yu, P.S.: COSNET: connecting heterogeneous social networks with local and global consistency. In: KDD, pp. 1485–1494 (2015)
Zhao, Q., Bhowmick, S.S., Zheng, X., Yi, K.: Characterizing and predicting community members from evolutionary and heterogeneous networks. In: CIKM, pp. 309–318 (2008)
Zheng, J., Liu, J., Shi, C., Zhuang, F., Li, J., Wu, B.: Dual similarity regularization for recommendation. In: PAKDD, pp. 542–554 (2016)
Zhou, D., Orshanskiy, S.A., Zha, H., Giles, C.L.: Co-ranking authors and documents in a heterogeneous network. In: ICDM, pp. 739–744 (2007)
Zhou, Y., Liu, L.: Social influence based clustering of heterogeneous information networks. In: KDD, pp. 338–346 (2013)
Zhou, Y., Liu, L.: Activity-edge centric multi-label classification for mining heterogeneous information networks. In: KDD, pp. 1276–1285 (2014)
Zhou, Y., Cheng, H., Yu, J.X.: Graph clustering based on structural/attribute similarities. In: VLDB, pp. 718–729 (2009)
Zhu, M., Zhu, T., Peng, Z., Yang, G., Xu, Y., Wang, S., Wang, X., Hong, X.: Relevance search on signed heterogeneous information network based on meta-path factorization. In: WAIM, pp. 181–192 (2015)
Zhuang, H., Zhang, J., Brova, G., Tang, J., Cam, H., Yan, X., Han, J.: Mining query-Based subnetwork outliers in heterogeneous information networks. In: ICDM, pp. 1127–1132 (2014)
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Shi, C., Yu, P.S. (2017). Survey of Current Developments . In: Heterogeneous Information Network Analysis and Applications. Data Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-56212-4_2
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