ArnetMiner: extraction and mining of academic social networks

Support-vector networks

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Support-Vector Networks

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Latent dirichlet allocation

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Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

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Modern Information Retrieval

Baeza-Yates, R. A., & Ribeiro-Neto, B. A. (1999) · Cited by 11,505

Support vector machines

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Probabilistic Latent Semantic Indexing

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Probabilistic latent semantic indexing

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An introduction to MCMC for machine learning.

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Supervised Topic ModelsPreprint

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H2CGL: Modeling dynamics of citation network for impact prediction

He, G., Xue, Z., Jiang, Z., Kang, Y., Zhao, S. X., & Lu, W. P. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103512 · Cited by 25

Towards Better Understanding of Academic Search

Khabsa, M., Wu, Z., & Giles, C. L. (2016) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/2910896.2910922 · Cited by 25

Behavior2Vec

Chen, H. (2018) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3184454 · Cited by 25

Logical Structure Recovery in Scholarly Articles with Rich Document Features

Luong, M.-T., Nguyen, T., & Kan, M. (2012) · IGI Global eBooks · doi:10.4018/978-1-4666-0900-6.ch014 · Cited by 25

The dynamic evolution of social ties and user-generated content: a case study on a Douban group

Shan, S., Ren, J., & Li, C. (2016) · Enterprise Information Systems · doi:10.1080/17517575.2016.1177204 · Cited by 25

Mining frequent neighborhood patterns in a large labeled graph

Han, J., & Wen, J.-R. (2013) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2505515.2505530 · Cited by 24

HINMINE: heterogeneous information network mining with information retrieval heuristics

Kralj, J., Robnik‐Šikonja, M., & Lavrač, N. (2017) · Journal of Intelligent Information Systems · doi:10.1007/s10844-017-0444-9 · Cited by 24

Discovering related scientific literature beyond semantic similarity: a new co-citation approach

Rodriguez-Prieto, O., Araujo, L., & Martínez-Romo, J. (2019) · Scientometrics · doi:10.1007/s11192-019-03125-9 · Cited by 24

Embedding-Based Recommendations on Scholarly Knowledge Graphs

Nayyeri, M., Vahdati, S., Zhou, X., Yazdi, H. S., & Lehmann, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49461-2_15 · Cited by 24

An Approach For Concept Drift Detection in a Graph Stream Using Discriminative Subgraphs

Paudel, R., & Eberle, W. (2020) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3406243 · Cited by 24

Geography of science: Competitiveness and inequality

Patelli, A., Napolitano, L., Cimini, G., & Gabrielli, A. (2022) · Journal of Informetrics · doi:10.1016/j.joi.2022.101357 · Cited by 24

FedGraphNN: A Federated Learning Benchmark System for Graph Neural Networks

He, C., Balasubramanian, K., Ceyani, E., Yang, C., Xie, H., Sun, L., He, L., Yang, L., Yu, P. S., Rong, Y., et al. (2021) · Cited by 24

Research trend prediction in computer science publications: a deep neural network approach

Taheri, S., & Aliakbary, S. (2022) · Scientometrics · doi:10.1007/s11192-021-04240-2 · Cited by 24

Exploiting Higher Order Multi-dimensional Relationships with Self-attention for Author Name Disambiguation

Pooja, K. M., Mondal, S., & Chandra, J. (2022) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3502730 · Cited by 24

Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction

Geng, H., Wang, D., Zhuang, F., Ming, X., Du, C., Jiang, T., Guo, H., & Liu, R. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557398 · Cited by 24

Accelerating k-Core Decomposition by a GPU

Ahmad, A., Yuan, L., Yan, D., Guo, G., Chen, J., & Zhang, C. (2023) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde55515.2023.00142 · Cited by 24

FORGE: Pre-Training Open Foundation Models for Science

Yin, J., Dash, S., Wang, F., & Shankar, M. A. (2023) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1145/3581784.3613215 · Cited by 24

BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection

Liu, J., He, M., Shang, X., Shi, J. Y., Cui, B., & Yin, H. (2024) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde60146.2024.00220 · Cited by 24

AHNG: Representation learning on attributed heterogeneous network

Liu, M., Liu, J., Chen, Y., Wang, M., Chen, H., & Zheng, Q. (2019) · Information Fusion · doi:10.1016/j.inffus.2019.01.005 · Cited by 24

Scholarly data mining: A systematic review of its applications

Dridi, A., Gaber, M. M., Azad, R. M. A., & Bhogal, J. (2020) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1395 · Cited by 24

Maximal Directed Quasi -Clique Mining

Guo, G., Yan, D., Yuan, L., Khalil, J. M., Long, C., Jiang, Z., & Zhou, Y. (2022) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde53745.2022.00188 · Cited by 24

ExpFinder: Finding experts by graph pattern matching

Fan, W., Wang, X., & Wu, Y. (2013) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2013.6544933 · Cited by 24

Mining Dual Networks

Wu, Y., Zhu, X., Li, L., Fan, W., Jin, R., & Zhang, X. (2016) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2785970 · Cited by 24

Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer ScientistsPreprint

Jadidi, M., Karimi, F., Lietz, H., & Wagner, C. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3063273 · Cited by 24

Review on Graph Feature Learning and Feature Extraction Techniques for Link Prediction.

Mutlu, E. Ç., & Oghaz, T. A. (2019) · Cited by 23

Network Embedding via Motifs

Shao, P. H., Yang, Y., Xu, S., & Wang, C. (2021) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3473911 · Cited by 23

Meta-path-based heterogeneous graph neural networks in academic network

Liang, X., Ma, Y., Cheng, G., Fan, C., Yang, Y., & Liu, Z. (2021) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-021-01465-8 · Cited by 23

Heterogeneous dynamical academic network for learning scientific impact propagation

Xu, X., Zhong, T., Li, C., Trajcevski, G., & Zhou, F. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107839 · Cited by 23

A2S2-GNN: Rigging GNN-Based Social Status by Adversarial Attacks in Signed Social Networks

Yin, X., Lin, W., Sun, K., Wei, C., & Chen, Y. (2022) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2022.3219342 · Cited by 23

Universal Option Models

Yao, H., Szepesvári, C., Sutton, R. S., Modayil, J., & Bhatnagar, S. (2014) · Cited by 23

Fast and Flexible Top- k Similarity Search on Large Networks

Zhang, J., Tang, J., Ma, C., Tong, H., Yu, J. S., Li, J., Luyten, W. H. M. L., & Moens, M. (2017) · ACM Transactions on Information Systems · doi:10.1145/3086695 · Cited by 23

SCSMiner: mining social coding sites for software developer recommendation with relevance propagation

Wan, Y., Chen, L., Xu, G., Zhao, Z., Tang, J., & Wu, J. (2018) · World Wide Web · doi:10.1007/s11280-018-0526-9 · Cited by 23

An integer linear programming model of reviewer assignment with research interest considerations

Jin, J., Niu, B., Ji, P., & Geng, Q. (2018) · Annals of Operations Research · doi:10.1007/s10479-018-2919-7 · Cited by 23

Multilevel Graph-Based Decision Making in Big Scholarly Data: An Approach to Identify Expert Reviewer, Finding Quality Impact Factor, Ranking Journals and Researchers

Rathore, M. M., Gul, M. J. J., Paul, A., Khan, A. A., Ahmad, R. W., Rodrigues, J. J. P. C., & Bakiras, S. (2018) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2018.2869458 · Cited by 23

Abnormal Event Detection via Heterogeneous Information Network Embedding

Fan, S., Shi, C., & Wang, X. (2018) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3269206.3269281 · Cited by 23

Content to Node: Self-Translation Network Embedding

He, Z., Liu, J., Zeng, Y., Wei, L., & Huang, Y. (2019) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2019.2932388 · Cited by 23

Keyphrase Generation: A Multi-Aspect Survey

Çano, E., & Bojar, O. (2019) · Conference of Open Innovations Association (FRUCT) · doi:10.23919/fruct48121.2019.8981519 · Cited by 23

spatial@linkedscience – Exploring the Research Field of GIScience with Linked Data

Keßler, C., Janowicz, K., & Kauppinen, T. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33024-7_8 · Cited by 23

Recommendation in Academia: A joint multi-relational model

Yang, Z., Yin, D., & Davison, B. D. (2014) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2014.6921643 · Cited by 23

Towards Social Network Extraction Using a Graph Database

Soussi, R., Aufaure, M.-A., & Zghal, H. B. (2010) · Databases, Knowledge, and Data Applications · doi:10.1109/dbkda.2010.19 · Cited by 23

Graph Anomaly Detection with Few Labels: A Data-Centric Approach

Ma, X., Li, R., Liu, F., Ding, K., Yang, J. Y., & Wu, J. X. (2024) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3637528.3671929 · Cited by 22

Citation interactions among computer science fields: a quantitative route to the rise and fall of scientific research

Chakraborty, T., Sikdar, S., Ganguly, N., & Mukherjee, A. (2014) · Social Network Analysis and Mining · doi:10.1007/s13278-014-0187-3 · Cited by 22

Hypergraph co-optimal transport: metric and categorical properties

Chowdhury, S., Needham, T., Semrad, E., Wang, B., & Zhou, Y. (2023) · Journal of Applied and Computational Topology · doi:10.1007/s41468-023-00142-9 · Cited by 22

Parallel Rule Discovery from Large Datasets by Sampling

Fan, W., Han, Z., Wang, Y., & Xie, M. (2022) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/3514221.3526165 · Cited by 22

OAG: Linking Entities Across Large-Scale Heterogeneous Knowledge Graphs

Zhang, F., Liu, X., Tang, J., Dong, Y., Yao, P., Zhang, J., Gu, X., Wang, Y., Kharlamov, E., Shao, B., et al. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2022.3222168 · Cited by 22

Correntropy-Induced Wasserstein GCN: Learning Graph Embedding via Domain Adaptation

Wang, W., Zhang, G., Han, H., & Zhang, C. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3293774 · Cited by 22

Research paper recommendation system based on multiple features from citation network

Kanwal, T., & Amjad, T. (2024) · Scientometrics · doi:10.1007/s11192-024-05109-w · Cited by 22

Researcher homepage classification using unlabeled data

Gollapalli, S. D., Caragea, C., Mitra, P., & Giles, C. L. (2013) · International World Wide Web Conference (WWW) · doi:10.1145/2488388.2488430 · Cited by 22

Endorsement deduction and ranking in social networks

Pérez‐Rosés, H., Sebé, F., & Ribó, J. M. (2015) · Computer Communications · doi:10.1016/j.comcom.2015.08.018 · Cited by 22

Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer

Liu, Y.-F., Hsu, C.-Y., & Wu, S.-H. (2015) · Cited by 22

Mining Query-Based Subnetwork Outliers in Heterogeneous Information Networks

Zhuang, H., Zhang, J., Brova, G., Tang, J., Çam, H., Yan, X., & Han, J. (2014) · Proceedings · doi:10.1109/icdm.2014.85 · Cited by 22

Inferring the Travel Purposes of Passenger Groups for Better Understanding of Passengers

Lin, Y., Wan, H., Jiang, R., Wu, Z., & Jia, X. (2014) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2014.2329422 · Cited by 22

Toward ontology-based personalization of a recommender system in social network

Kadima, H., & Malek, M. (2010) · International Conference of Soft Computing and Pattern Recognition (SoCPaR) · doi:10.1109/socpar.2010.5685957 · Cited by 22

Entity Type Recognition for Heterogeneous Semantic Graphs

Sleeman, J., Finin, T., & Joshi, A. (2015) · AI Magazine · doi:10.1609/aimag.v36i1.2569 · Cited by 22

Trend-Based Citation Count Prediction for Research Articles

Li, C., Lin, Y.-J., Yan, R., & Yeh, M.-Y. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-18038-0_51 · Cited by 22

A multilayered approach for link prediction in heterogeneous complex networks

Shakibian, H., Charkari, N. M., & Jalili, S. (2016) · Journal of Computational Science · doi:10.1016/j.jocs.2016.10.001 · Cited by 22

Bibliometrics, Information Retrieval and Natural Language Processing: Natural Synergies to Support Digital Library Research.

Wolfram, D. (2016) · Cited by 22

Joint Model Feature Regression and Topic Learning for Global Citation Recommendation

Dai, T., Zhu, L., Wang, Y., Zhang, H., Cai, X., & Zheng, Y. (2018) · IEEE Access · doi:10.1109/access.2018.2884981 · Cited by 22

A Pattern-Based Academic Reviewer Recommendation Combining Author-Paper and Diversity Metrics

Musa, I., Park, K. H., Lee, J. Y., & Ryu, K. H. (2019) · IEEE Access · doi:10.1109/access.2019.2894680 · Cited by 22

Neural Embedding Propagation on Heterogeneous Networks

Yang, C., Zhang, J., & Han, J. (2019) · Proceedings · doi:10.1109/icdm.2019.00080 · Cited by 22

Early-stage reciprocity in sustainable scientific collaboration

Wang, W. W., Ren, J. F., Alrashoud, M. R., Xia, F., Mao, M., & Tolba, A. K. R. (2020) · Journal of Informetrics · doi:10.1016/j.joi.2020.101041 · Cited by 22

CONNA: Addressing Name Disambiguation on the Fly

Chen, B., Zhang, J., Tang, J., Cai, L., Wang, Z., Zhao, S. G., Chen, H., & Li, C. (2020) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2020.3021256 · Cited by 22

Prediction of new scientific collaborations through multiplex networks

Tuninetti, M., Aleta, A., Paolotti, D., Moreno, Y., & Starnini, M. (2021) · EPJ Data Science · doi:10.1140/epjds/s13688-021-00282-x · Cited by 22

The LExR Collection for Expertise Retrieval in Academia

Mangaravite, V., Santos, R. L. T., Sandin, I., Gonçalves, M. A., & Laender, A. H. F. (2016) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2911451.2914678 · Cited by 22

StoryRoleNet: Social Network Construction of Role Relationship in Video

Lv, J., Wu, B., Zhou, L., & Wang, H. (2018) · IEEE Access · doi:10.1109/access.2018.2832087 · Cited by 22

ExplaiNE: An Approach for Explaining Network Embedding-based Link PredictionsPreprint

Kang, B., Lijffijt, J., & Bie, T. D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.12694 · Cited by 22

Disentangled Dynamic Graph Attention Network for Out-of-Distribution Sequential Recommendation

Zhang, Z., Wang, X. Y., Chen, H., Li, H., & Zhu, W. (2024) · ACM Transactions on Information Systems · doi:10.1145/3701988 · Cited by 21

RankTopic: Ranking Based Topic Modeling

Duan, D., Li, Y., Li, R., Zhang, R., & Wen, A. (2012) · Proceedings · doi:10.1109/icdm.2012.12 · Cited by 21

AMiner

Tang, J. (2016) · International World Wide Web Conference (WWW) · doi:10.1145/2872518.2890513 · Cited by 21

ScientoBASE: a framework and model for computing scholastic indicators of non-local influence of journals via native data acquisition algorithms

Ginde, G., Saha, S., Mathur, A., Venkatagiri, S., Vadakkepat, S., Narasimhamurthy, A. M., & Sagar, B. S. D. (2016) · Scientometrics · doi:10.1007/s11192-016-2006-2 · Cited by 21

Supervised Learning to Aggregate Data With the Sugeno Integral

Ga̧golewski, M., James, S., & Beliakov, G. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2895565 · Cited by 21

Collaborative Graph Neural Networks for Attributed Network Embedding

Tan, Q., Zhang, X., Huang, X. X., Chen, H., Li, J., & Hu, X. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3298002 · Cited by 21

Multi-view enhanced zero-shot node classification

Wang, J., Wu, L., Zhao, H., & Jia, N. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103479 · Cited by 21

Link Prediction in a Modified Heterogeneous Bibliographic Network

Lee, J. B., & Adorna, H. N. (2012) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2012.78 · Cited by 21

The use of a graph‐based system to improve bibliographic information retrieval: System design, implementation, and evaluation

Zhu, Y., Yan, E., & Song, I. (2016) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23677 · Cited by 21

A Survey on Context Learning

Xun, G., Jia, X., Gopalakrishnan, V., & Zhang, A. (2016) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2016.2614508 · Cited by 21

Identifying the Academic Rising Stars via Pairwise Citation Increment Ranking

Zhang, C., Liu, C., Yu, L., Zhang, Z., & Zhou, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-63579-8_36 · Cited by 21

Network Connectivity Optimization

Chen, C., Peng, R., Ying, L., & Tong, H. (2018) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3219819.3220019 · Cited by 21

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS

Arrigo, F., & Tudisco, F. (2019) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611975673.42 · Cited by 21

The NLP4NLP Corpus (I): 50 Years of Publication, Collaboration and Citation in Speech and Language Processing

Mariani, J., Francopoulo, G., & Paroubek, P. (2019) · Frontiers in Research Metrics and Analytics · doi:10.3389/frma.2018.00036 · Cited by 21

Structural Diversity and Homophily

Dong, Y., Johnson, R. A., Xu, J., & Chawla, N. V. (2017) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3097983.3098116 · Cited by 21

Effect of forename string on author name disambiguation

Kim, J., & Kim, J. (2019) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24298 · Cited by 21

Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes

Purwitasari, D., Fatichah, C., Sumpeno, S., Steglich, C., & Purnomo, M. H. (2020) · Scientometrics · doi:10.1007/s11192-019-03342-2 · Cited by 21

Topological Simplifications of Hypergraphs

Zhou, Y., Rathore, A., Purvine, E., & Wang, B. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3153895 · Cited by 21

A decade of Semantic Web research through the lenses of a mixed methods approach

Kirrane, S., Sabou, M., Fernández, J. D., Osborne, F., Robin, C., Buitelaar, P., Motta, E., & Axel Polleres, A. (2020) · Semantic Web · doi:10.3233/sw-200371 · Cited by 21

Automatically generating reading lists

Jardine, J. G. (2014) · CL Technical Reports · doi:10.48456/tr-848 · Cited by 21

Diffusion Maps for Textual Network EmbeddingPreprint

Zhang, X., Li, Y., Shen, D., & Carin, L. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.09906 · Cited by 21

Synthesizing global and local perspectives in contrastive learning for graph anomaly detection

Yang, Q., Yu, H., Liu, Z., Li, P., Chen, X., & Luo, X. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113289 · Cited by 20

Discovering latent commercial networks from online financial news articles

Xia, Y., Su, W., Lau, R. Y. K., & Liu, Y. (2011) · Enterprise Information Systems · doi:10.1080/17517575.2011.621093 · Cited by 20

Multi-task network embedding

Xu, L., Wei, X., Cao, J., & Yu, P. S. (2018) · International Journal of Data Science and Analytics · doi:10.1007/s41060-018-0166-2 · Cited by 20

Domain Adaptive Graph Infomax via Conditional Adversarial Networks

Xiao, J., Dai, Q., Xie, X., Dou, Q., Kwok, K., & Lam, J. (2022) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2022.3201529 · Cited by 20

Few-shot Node Classification with Extremely Weak Supervision

Wang, S., Dong, Y., Ding, K., Chen, C., & Li, J. (2023) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3539597.3570435 · Cited by 20

DyHNet: Learning dynamic heterogeneous network representations

Nguyen, H., Rad, R. H., Zarrinkalam, F., & Bagheri, E. (2023) · Information Sciences · doi:10.1016/j.ins.2023.119371 · Cited by 20

Efficient and Effective Edge-wise Graph Representation Learning

Wang, H., Yang, R., Huang, K., & Xiao, X. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599321 · Cited by 20

Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation

Zhang, Z., Liu, M., Wang, A., Chen, H., Li, Z., Bu, J., & He, B. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589334.3645507 · Cited by 20

An academic recommender system on large citation data based on clustering, graph modeling and deep learning

Stergiopoulos, V., Vassilakopoulos, M. G., Tousidou, E., & Corral, A. (2024) · Knowledge and Information Systems · doi:10.1007/s10115-024-02094-7 · Cited by 20

Development of multidimensional academic information networks with a novel data cube based modeling method

Kaya, M., & Alhajj, R. (2013) · Information Sciences · doi:10.1016/j.ins.2013.11.012 · Cited by 20

Topic-level social network search

Tang, J., Wu, S., Gao, B., & Wan, Y. (2011) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2020408.2020532 · Cited by 20

Integration of scientific and social networks

Neshati, M., Hiemstra, D., Asgari, E., & Beigy, H. (2013) · World Wide Web · doi:10.1007/s11280-013-0229-1 · Cited by 20

A Supervised Learning Method for Prediction Citation Count of Scientists in Citation Networks

Bütün, E., Kaya, M., & Alhajj, R. (2017) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3110025.3110160 · Cited by 20

Extraction and mining of an academic social network

Tang, J., Zhang, J., Yao, L., & Li, J. (2008) · International World Wide Web Conference (WWW) · doi:10.1145/1367497.1367722 · Cited by 48

BArnetminer: Extraction and mining of academic social networks

Tang, J., Zhang, J., Yao, L., & Li, J. (2014)

AMiner

Tang, J. (2016) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/2835776.2835849 · Cited by 60

ArnetMiner: Deep Mining for Academic Social Networks

Tang, J., & Li, J. (2015) · Synthesis lectures on data, semantics and knowledge · doi:10.1007/978-3-031-79462-9_5

AMiner: Search and Mining of Academic Social Networks

Wan, H., Zhang, Y., Zhang, J., & Tang, J. (2019) · Data Intelligence · doi:10.1162/dint_a_00006 · Cited by 81