ArnetMiner: extraction and mining of academic social networks

Support-vector networks

Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421

Support-Vector Networks

Cortes, C., & Vapnik, V. N. (1995) · Machine Learning · doi:10.1023/a:1022627411411 · Cited by 34,565

Latent dirichlet allocation

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

Lafferty, J., McCallum, A., & Pereira, F. C. N. (2001) · ScholarlyCommons (University of Pennsylvania) · Cited by 12,935

Modern Information Retrieval

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

Support vector machines

Hearst, M. A., Dumais, S. T., Osuna, E., Platt, J., & Scholkopf, B. (1998) · IEEE Intelligent Systems and their Applications · doi:10.1109/5254.708428 · Cited by 7,243

Probabilistic Latent Semantic Indexing

Hofmann, T. (2017) · ACM SIGIR Forum · doi:10.1145/3130348.3130370 · Cited by 3,988

Probabilistic latent semantic indexing

Hofmann, T. (1999) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/312624.312649 · Cited by 3,975

An introduction to MCMC for machine learning.

Andrieu, C., de Freitas, N., Doucet, A., & Jordan, M. I. (2003) · Machine Learning · doi:10.1023/a:1020281327116 · Cited by 2,451

Supervised Topic ModelsPreprint

Blei, D., & McAuliffe, J. D. (2007) · Neural Information Processing Systems · doi:10.48550/arxiv.1003.0783 · Cited by 1,860

Modeling Attackers Based on Heterogenous Graph through Malicious HTTP Requests

Ao, S., He, Y., Luo, N., Wang, X., Jiang, Z., & Jiang, J. (2021) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd49262.2021.9437624 · Cited by 1

Link Perspective Based Network Embedding for Link Prediction

Ni, Q., Ma, L., Ye, Y., Wang, Y., & Bu, Z. (2020) · doi:10.1145/3449301.3449781 · Cited by 1

Should I Stay or Should I Go: Predicting Changes in Cluster Membership

Tsoukanara, E., Koloniari, G., & Pitoura, E. (2021) · Communications in computer and information science · doi:10.1007/978-981-16-8143-1_1 · Cited by 1

Bayesian Belief Network Model Using Sematic Concept for Expert Finding

Zheng, W., Hou, H., Wu, N., & Sun, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-82147-0_10 · Cited by 1

Co-embedding: Discovering Communities on Bipartite Graphs Through Projection

Candel, G., & Naccache, D. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-98012-2_9 · Cited by 1

ProcK: Machine Learning for Knowledge-Intensive Processes

Jacobs, T., Yu, J., Gastinger, J., & Sztyler, T. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26390-3_7 · Cited by 1

Sequence Contained Heterogeneous Graph Neural Network

Zhang, S., Huang, T., & Wang, D. (2021) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn52387.2021.9533391 · Cited by 1

VeTo+: improved expert set expansion in academia

Chatzopoulos, S., Vergoulis, T., Dalamagas, T., & Tryfonopoulos, C. (2021) · International Journal on Digital Libraries · doi:10.1007/s00799-021-00318-7 · Cited by 1

Temporalizing static graph autoencoders to handle temporal networks

Haddad, M., Bothorel, C., Lenca, P., & Bedart, D. (2021) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3487351.3488333 · Cited by 1

Multi-granular attributed network representation learning

Zou, J., Du, Z., & Zhao, S. G. (2022) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-022-01507-9 · Cited by 1

Who to Watch Next: Two-side Interactive Networks for Live Broadcast Recommendation

Jin, J., Chen, X., Chen, Y., Zhang, W., Rui, R., Jiang, Z., Su, Z., & Yu, Y. (2022) · International World Wide Web Conference (WWW) · doi:10.1145/3485447.3511939 · Cited by 1

A Strategy for Identifying Specialists in Scientific Data Repositories

de Sousa, S. J., Dias, T. M. R., & Pinto, A. L. (2022) · Mobile Networks and Applications · doi:10.1007/s11036-022-01964-0 · Cited by 1

A Technical Review and Framework Design for Influence Extraction from Social Networks

Saini, A., & Sornalakshmi, K. (2022) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-5652-1_46 · Cited by 1

IDS: An Intelligent Data Semantics System for Communication Link Prediction in SIoT

Wang, B., Huang, Z., Zhao, D., Huang, K., Song, M.-X., Jiang, Q., & Xiong, N. N. (2021) · International Conference on Mobility, Sensing and Networking (MSN) · doi:10.1109/msn53354.2021.00051 · Cited by 1

Learning cascaded influence under partial monitoring

Zhang, J., Ma, J., & Tang, J. (2016) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2016.7752243 · Cited by 1

ENDASh: Embedding Neighbourhood Dissimilarity with Attribute Shuffling for Graph Anomaly Detection

Wang, Q., Salehi, M., Low, J. S., Buntine, W., & Leckie, C. A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-05936-0_2 · Cited by 1

Network Embedding with Dual Generation Tasks

Li, N., Liu, J., He, Z., Zhang, C., & Xie, J. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2022.3187851 · Cited by 1

Report on the 8th International Workshop on Bibliometric-Enhanced Information Retrieval (BIR 2019)

Cabanac, G., Frommholz, I., & Mayr, P. (2019) · ACM SIGIR Forum · doi:10.1145/3458537.3458540 · Cited by 1

SurvAnnT: Facilitating Community-Led Scientific Surveys and Annotations

Tzerefos, A., Kanellos, I., Chatzopoulos, S., Dalamagas, T., & Vergoulis, T. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16802-4_61 · Cited by 1

Improving graph prototypical network using active learning

Solgi, M., & Seydi, V. (2022) · Progress in Artificial Intelligence · doi:10.1007/s13748-022-00293-3 · Cited by 1

Community Detection in Edge-Labeled Graphs

Kumpulainen, I., & Tatti, N. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-18840-4_33 · Cited by 1

The profit and risk in the interdisciplinary behavior

Fu, C., Luo, H., Liang, X., & Yu, S. (2023) · Frontiers in Physics · doi:10.3389/fphy.2023.1107446 · Cited by 1

An FPGA-based Accelerator for Regular Path Queries over Edge-labeled Graphs

Miura, K., Kobayashi, R., Amagasa, T., Kitagawa, H., Fujita, N., & Boku, T. (2022) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata55660.2022.10020406 · Cited by 1

A Community Detection Approach for Academic Social Network: the Case of the Cross-Strait Academic Conference Network

Zhang, X., Xu, L., Gao, M., Fan, J., & Sun, H. (2022) · doi:10.1109/cecit58139.2022.00044 · Cited by 1

A New Approach for Semi-External Topological Sorting on Big Graphs

Gao, T., Li, J., & Ma, H. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2023.3274528 · Cited by 1

Country-Level Collaboration Patterns of Social Computing Scholars

Chen, J., Shao, Y., Gong, Q., & Chen, Y. (2023) · Communications in computer and information science · doi:10.1007/978-981-99-2356-4_14 · Cited by 1

Using Supervised Learning to Estimate the Acceptance of Research Papers by Conferences

Katyayan, S. S., & Singh, I. (2022) · IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) · doi:10.1109/iatmsi56455.2022.10119439 · Cited by 1

Targeted Training for Multi-organization Recommendation

Tomlinson, K., Wan, M., Lu, C., Hecht, B. J., Teevan, J. B., & Yang, L. (2023) · ACM Transactions on Recommender Systems · doi:10.1145/3603508 · Cited by 1

A Field of Study-Centric Approach to Evaluating Paper Similarity

Ma, J., & Chen, K. (2023) · IEEE International Conference on Electronic Technology, Communication and Information (ICETCI) · doi:10.1109/icetci57876.2023.10176424 · Cited by 1

TNSEIR: A SEIR pattern-based embedding approach for temporal network

Lei, W., Zhu, Y., & Peng, Q. (2023) · Applied Intelligence · doi:10.1007/s10489-023-04842-8 · Cited by 1

Few-Shot Node Classification on Attributed Networks Based on Prototypical Network

Zhao, Y., Zhang, G., & Wang, J. (2022) · IEEE Smart World Congress (SWC) · doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00044 · Cited by 1

Research on Alignment Method of Civil Aviation Equipment Domain and General Knowledge Graph Entity Based on Graph Neural Network Embedding

Guo, D., Wu, T., & Fu, A. (2023) · International Symposium on Intelligent Robotics and Systems (ISoIRS) · doi:10.1109/isoirs59890.2023.00052 · Cited by 1

Dense subgraphs induced by edge labels

Kumpulainen, I., & Tatti, N. (2023) · Machine Learning · doi:10.1007/s10994-023-06377-y · Cited by 1

DYANE: DYnamic Attributed Node rolEs Generative Model

Zeno, G., & Neville, J. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3614858 · Cited by 1

A Scholarly Information Retrieval System Incorporating Recommendation with Semantic Similarity

Lan, Y., Lin, R., & Mao, C. (2024) · Communications in computer and information science · doi:10.1007/978-981-99-9637-7_22 · Cited by 1

Recommender Systems based on Parallel and Distributed Deep Learning

Stergiopoulos, V., Tousidou, E., & Corral, A. (2023) · Pan-Hellenic Conference on Progress in Computing and Informatics (PCI) · doi:10.1145/3635059.3635069 · Cited by 1

Community Detection Methods Based on Exploiting Attributes and Interactions on Social Networks: A Survey and Future Directions

Truong, H. B., Ivanović, M. D., & Tran, C. (2024) · Vietnam Journal of Computer Science · doi:10.1142/s2196888824300011 · Cited by 1

On the Scale-Free Property of Citation Networks: An Empirical Study

Zhong, X., & Liang, H. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589335.3651541 · Cited by 1

Knowledge Base Embeddings for a Recommendation Based on Overlapping Knowledge and Graph Learning

Zhao, Y., & Wang, T. (2024) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-024-09573-7 · Cited by 1

Power on graph: Mining power relationship via user interaction correlation

Zang, Y., Ren, L., Wu, J., Xiao, Y., & Hu, R. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.126348 · Cited by 1

Clustering and Topic Discovery of Multiway Data via Joint-NCMTF

Cobb, B., Velasquez, R., Vuduc, R. W., & Park, H. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825741 · Cited by 1

Neural RELAGGS

Pensel, L., & Krämer, S. (2025) · Machine Learning · doi:10.1007/s10994-025-06753-w · Cited by 1

Neighbourhood Distinctiveness: An Initial Study

Hecker, A., Carstens, C. J., & Horadam, K. J. (2015) · Studies in computational intelligence · doi:10.1007/978-3-319-16112-9_10 · Cited by 1

Generalized random Surfer-Pair models

Narayanaswami, S. K., Ravindran, B., & Ramaiyan, V. (2019) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3341161.3342914 · Cited by 1

Improving Academic Homepage Identification from the Web Using Neural Networks

Zhao, J., Liu, T., & Shi, J. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22750-0_50 · Cited by 1

SciTo Trends: Visualising Scientific Topic Trends

Chatzopoulos, S., Deligiannis, P. K., Vergoulis, T., Kanellos, I., Tryfonopoulos, C., & Dalamagas, T. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30760-8_41 · Cited by 1

Effective Author Ranking Using Average of Different h-Index Variants

Chandra, P. K., Jha, V., & Abhishek, K. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-4032-5_6 · Cited by 1

Semantic-driven bibliometric techniques for co-citation analysis

Taieb, M. A. H., Aouicha, M. B., & Turki, H. (2020) · International Journal of Hybrid Intelligent Systems · doi:10.3233/his-200288 · Cited by 1

Attributed Heterogeneous Network Embedding for Link Prediction

Wang, T., Yuan, W., & Guan, D. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69886-7_9 · Cited by 1

Ranking on Network of Heterogeneous Information Networks

Xu, Z., Zhang, S., Xia, Y., Xiong, L., & Tong, H. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9378121 · Cited by 1

Social Network Opinion and Posts Mining for Community Preference Discovery

Mumu, T. (2013) · Scholarship at UWindsor (University of Windsor) · Cited by 1

Modeling the Interplay Between Individual Behavior and Network DistributionsPreprint

Yang, Y., Tang, J., Dong, Y., Mei, Q., Johnson, R. A., & Chawla, N. V. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.02562 · Cited by 1

Fast Algorithms for Game-Theoretic Centrality MeasuresPreprint

Szczepański, P. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1512.01764 · Cited by 1

Hierarchical Bayesian topic modeling with sentiment and author extension

Yang, M. (2016) · K-State Research Exchange (Kansas State University) · Cited by 1

Social network extraction using Web Mining Techniques

Arif, T. (2012) · Shodhgangotri · Cited by 1

An Agent-Oriented Architecture for Researcher Profiling and Association Using Semantic Web Technologies

Adnan, S., Tahir, A., Basharat, A., & de Cesare, S. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-16089-9_5 · Cited by 1

A Search/Crawl Framework for Automatically Acquiring Scientific DocumentsPreprint

Gollapalli, S. D., Patel, K., & Caragea, C. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1604.05005 · Cited by 1

Network Data Collected via Web

Coromina, L., Hlebec, V., Kogovšek, T., & Coenders, G. (2018) · Springer eBooks · doi:10.1007/978-1-4939-7131-2_397 · Cited by 1

Understanding Tree: a tool to estimate one's understanding of knowledgePreprint

Liu, G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.07714 · Cited by 1

My Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text CollectionsPreprint

Risch, J., & Krestel, R. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.11240 · Cited by 1

Graph Pattern Mining and Learning through User-defined Relations (Extended Version)Preprint

Teixeira, C. H. C., Cotta, L., Ribeiro, B., & Meira, W. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.05241 · Cited by 1

Report on the 7th International Workshop on Bibliometric-enhanced Information Retrieval (BIR 2018)Preprint

Mayr, P., Frommholz, I., & Cabanac, G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1804.03713 · Cited by 1

Adversarial Context Aware Network Embeddings for Textual NetworksPreprint

Gracious, T., & Dukkipati, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.02665 · Cited by 1

NameRec*: Highly Accurate and Fine-grained Person Name RecognitionPreprint

Zhang, R., Dai, Y., & Liu, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.11360 · Cited by 1

Team Power and Hierarchy: Understanding Team Success.Preprint

Xu, H., Bu, Y., Liu, M., Zhang, C., Sun, M., Zhang, Y., Meyer, E. T., Salas, E., & Ding, Y. (2021) · arXiv (Cornell University) · Cited by 1

Multi-facet graph mining with contextualized projections

Yang, C. (2020) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 1

Unsupervised Domain-adaptive Hash for NetworksPreprint

He, T., Gao, L., Song, J., & Li, Y.-F. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.09136 · Cited by 1

Index $t$-SNE: Tracking Dynamics of High-Dimensional Datasets with Coherent Embeddings

Candel, G., & Naccache, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.10538 · Cited by 1

Learning Asymmetric Embedding for Attributed Networks Via Convolutional Neural NetworkPreprint

Radmanesh, M., Ghorbanzadeh, H., Rezaei, A. A., Jalili, M., & Yu, X. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4188469 · Cited by 1

Denoising Attention for Query-aware User Modeling in Personalized SearchPreprint

Bassani, E., Kasela, P., & Pasi, G. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2308.15968 · Cited by 1

Degan - Decomposition-Based Unified Anomaly Detection in Static NetworksPreprint

Tüzen, A., & Yaslan, Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4666801 · Cited by 1

Autocpp: A Novel Framework for Cascade Popularity Prediction Via Bi-Level Graph Augmentation and Neural Architecture SearchPreprint

Xu, H., Wang, S., Gao, C., Li, X., & Wang, Z. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4750352 · Cited by 1

OmniReview: A Large-scale Benchmark and LLM-enhanced Framework for Realistic Reviewer RecommendationPreprint

Huang, Y., Sun, P., Chen, Z., Tang, Z., & Chu, X. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2602.08896 · Cited by 1

Graph Representation Learning : from Kernel to Neural Networks

Wu, C. (2021) · theses.fr (ABES) · doi:10.70675/e0b743a0z2afcz4bbezb114z8066ef87a293 · Cited by 1

DeepConnect: A Visual Analytics System for Bridging Interdisciplinary Research CollaborationsPreprint

Feng, Y., Shao, Z., Sun, Y., Tang, Y., & Tung, A. K. H. (2026) · arXiv (Cornell University) · Cited by 1

Discovery of knowledge collaborative communities for multi-domain problem solving

Yuan, S. (2010) · Research Online (University of Wollongong)

Mining and Analyzing the Academic Network

Yang, Z. (2014)

Research network analyses of Indian computer science researchers: Problems and solutions

Jaimini, U., Ojha, V., Pant, M., & Abraham, A. (2015)

Intelligent System Based Assessments of Academic Journals

Pan, S. (2015)

Design and Considerations of a Searching Software

Zhang, H. (2015) · Transactions on machine learning and data mining

MYE: Missing Year Estimation in Academic Social NetworksPreprint

Fu, T. Z. J., Ying, Q., & Chiu, D. M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1306.4066

Evaluating community structure in large network with random walksPreprint

Li, J. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.2698

Enhanced Conference Organization Based On Correlation Of Web Information And Ontology Based Expertise Search

Noureddine, H., Sokhn, M., Jarkass, I., Mugellini, E., & Khaled, O. A. (2013) · ArODES (HES-SO (https://www.hes-so.ch/)) · doi:10.5281/zenodo.1079525

Resource-Bounded Information Acquisition and Learning

H. Kanani, P. (2012) · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · doi:10.7275/6fxh-hn85

Regional subgraph discovery in social networks

Li, C., Shan, M.-K., & Lin, S.-D. (2012) · International World Wide Web Conference (WWW) · doi:10.1145/2187980.2188128

Learning reputation in an authorship network

Dhanjal, C., & Clémençon, S. (2014) · ACM Symposium on Applied Computing · doi:10.1145/2554850.2555098

Eclectic Method for Developing Optimum ANN's

Mota-Hernández, C. I., Alvarado-Corona, R., & Contreras-Troya, T. I. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.02.142

SAE

Yang, Y., Wang, J., Zhang, Y., Chen, W., Zhang, J., Zhuang, H., Yang, Z., Ma, B., Fang, Z., Wu, S., et al. (2013) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2487575.2487720

A New Vision-Based Method for Extracting Academic Information from Conference Web Pages

Wang, P., Zhou, M., You, Y., & Zhang, X. (2012) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai.2012.138

A conversation with Professors Deyi Li and Jie Tang

Li, D., & Tang, J. (2012) · ACM SIGKDD Explorations Newsletter · doi:10.1145/2207243.2207257

IRIS2: A Semantic Search Engine That Does Rational Research

Wang, W., & Liang, H. (2014) · IEEE International Conference on Computational Science and Engineering (CSE) · doi:10.1109/cse.2014.62

A Novel Method for Mining the Advisor-Student Relationships in Academic Social Network

Wang, Y., & Liu, X. L. (2013) · Advanced materials research · doi:10.4028/www.scientific.net/amr.655-657.1795

Term Filtering with Bounded Error

Yang, Z., Li, W., Tang, J., & Li, J. (2010) · Proceedings · doi:10.1109/icdm.2010.131

Tracking individual behaviors in networks: An experimental demonstration

Balasingam, B., Willett, P., & Bar‐Shalom, Y. (2012) · Scholarship at UWindsor (University of Windsor)

Topic Analysis for Online Reviews with an Author-Experience-Object-Topic Model

Zhang, Y., Ji, D., Su, Y., & Hu, P. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-25631-8_28

RENS – Enabling a Robot to Identify a Person

Yan, X., Jeschke, S., Dubey, A., Wilke, M., & Schütze, H. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-10817-4_5

Impact of consolidating Web based social networks on derived trust factors

Imran, M., David, M., & Tiropanis, T. (2012) · ePrints Soton (University of Southampton)

FP-Tree based Association Rule Mining in Academic Social Networks to Refine RDF Framework and FOAF

SobhaRani, K., Raju, K. V. S. V. N., & Kumari, V. V. (2013) · International Journal of Computer Applications · doi:10.5120/12449-9168

Network Modeling and Visualization System Based on Chinese Text

Shi, C., Wu, G., Wu, B., & Zhong, C. (2009) · International Conference on Information Engineering and Computer Science · doi:10.1109/iciecs.2009.5365049

Meta-Scraping: Two Technological Approaches to Support Meta-analyses

Nimon, K., Caragea, C., & Oswald, F. L. (2013) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · doi:10.9776/13311

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