A Method of Extracting The Semi-structured Data Implication Rules

SPADE: An Efficient Algorithm for Mining Frequent Sequences

Zaki, M. J. (2001) · Machine Learning · doi:10.1023/a:1007652502315 · Cited by 1,864 · see citing works

Approximate frequency counts over data streams

Manku, G. S., & Motwani, R. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2367502.2367508 · Cited by 1,187 · see citing works

DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases

Goldman, R., & Widom, J. (1997) · Cited by 1,136 · see citing works

Approximate Frequency Counts over Data Streams

Manku, G. S., & Motwani, R. (2002) · Elsevier eBooks · doi:10.1016/b978-155860869-6/50038-x · Cited by 941 · see citing works

Object exchange across heterogeneous information sources

Papakonstantinou, Y., García-Molina, H., & Widom, J. (2002) · Proceedings - International Conference on Data Engineering · doi:10.1109/icde.1995.380386 · Cited by 755 · see citing works

Relational Learning of Pattern-Match Rules for Information Extraction.

Califf, M. E., & Mooney, R. J. (1997) · Cited by 507 · see citing works

X-Diff: an effective change detection algorithm for XML documents

Wang, Y., DeWitt, D. J., & Cai, J. (2004) · Proceedings - International Conference on Data Engineering · doi:10.1109/icde.2003.1260818 · Cited by 349 · see citing works

DOM-based content extraction of HTML documents

Gupta, S., Kaiser, G. E., Neistadt, D., & Grimm, P. (2003) · International World Wide Web Conference (WWW) · doi:10.1145/775152.775182 · Cited by 318 · see citing works

Extracting schema from semistructured data

Nestorov, S., Abiteboul, S., & Motwani, R. (1998) · Proceedings - ACM-SIGMOD International Conference on Management of Data · doi:10.1145/276304.276331 · Cited by 224 · see citing works

TreeFinder: a first step towards XML data mining

Termier, A., Rousset, M.-C., & Sébag, M. (2003) · Proceedings · doi:10.1109/icdm.2002.1183987 · Cited by 183 · see citing works

Mining closed and maximal frequent subtrees from databases of labeled rooted trees

Chi, Y., Xia, Y., Yang, Y., & Muntz, R. R. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.30 · Cited by 131 · see citing works

Ozone: Integrating Structured and Semistructured Data

Lahiri, T., Abiteboul, S., & Widom, J. (2000) · Lecture notes in computer science · doi:10.1007/3-540-44543-9_18 · Cited by 70 · see citing works

Extracting schema from semistructured data

Nestorov, S., Abiteboul, S., & Motwani, R. (1998) · ACM SIGMOD Record · doi:10.1145/276305.276331 · Cited by 39 · see citing works

An analytical review of XML association rules mining

Moradi, M., & Keyvanpour, M. R. (2013) · Artificial Intelligence Review · doi:10.1007/s10462-012-9376-5 · Cited by 23 · see citing works

Spectroscopy and energy transfer parameters of Tm3+- and Ho3+-doped Ba2NaNb5O15 single crystals

Bigotta, S., Toncelli, A., Tonelli, M., Cavalli, E., & Bovero, E. (2007) · Optical Materials · doi:10.1016/j.optmat.2006.11.040 · Cited by 12 · see citing works

Parallel Implementation of FP Growth Algorithm on XML Data Using Multiple GPU

Rathi, S., & Dhote, C. A. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-81-322-2250-7_58 · Cited by 5 · see citing works

Efficient Mining of Frequent Closed XML Query Pattern

Feng, J., Qian, Q., Wang, J., & Zhou, L. (2007) · Journal of Computer Science and Technology · doi:10.1007/s11390-007-9081-z · Cited by 5 · see citing works

DOM and SAX Technology in XML Programming

Jun-lan, Z. (2004) · Jisuanji gongcheng · Cited by 3 · see citing works

PXML-Miner: A Projection-Based Interesting XML Rule Mining Technique

Sasikala, D., & Premalatha, K. (2014) · Data Science Journal · doi:10.2481/dsj.13-017 · Cited by 2 · see citing works

A Method for Finding Implicating Rules Based on the Genetic Algorithm

Jun, Z., Li, S., Hong-yan, M., & Liu, H. (2007) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2007.61 · Cited by 2 · see citing works

Design and Implementation of an Efficient Wrapper for Web Data Extraction

Zhang, S. (2009) · Computer Technology and Development · Cited by 1 · see citing works

Ready or not, AI comes—an interview study of organizational AI readiness factors

Jöhnk, J., Weißert, M., & Wyrtki, K. (2021) · Business & Information Systems Engineering · doi:10.1007/s12599-020-00676-7 · Cited by 637 · see citing works

Context Deep Neural Network Model for Predicting Depression Risk Using Multiple Regression

Baek, J.-W., & Chung, K. (2020) · IEEE Access · doi:10.1109/access.2020.2968393 · Cited by 104 · see citing works

Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Munodawafa, R. T., & Johl, S. K. (2019) · Sustainability · doi:10.3390/su11154254 · Cited by 58 · see citing works

Advanced big-data/machine-learning techniques for optimization and performance enhancement of the heat pipe technology – A review and prospective study

Wang, Z., Zhao, X., Han, Z., Luo, L. C., Xiang, J., Zheng, S., Liu, G., Yu, M., Cui, Y., Shittu, S., et al. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.116969 · Cited by 54 · see citing works

Big Data Analytics and Its Role to Support Groundwater Management in the Southern African Development Community

Gaffoor, Z., Pietersen, K., Jovanovic, N. Z., Bagula, A., & Kanyerere, T. (2020) · Water · doi:10.3390/w12102796 · Cited by 42 · see citing works

Factors influencing readiness for artificial intelligence: a systematic literature review

Ali, W., & Khan, A. Z. (2024) · Data Science and Management · doi:10.1016/j.dsm.2024.09.005 · Cited by 53 · see citing works

A Novel Metadata Based Multi-Label Document Classification Technique

Sajid, N. A., Ahmad, M., Rahman, A., Zaman, G., Ahmed, M. S., Ibrahim, N. M., Ahmed, M. I. B., Krishnasamy, G., Alzaher, R., Alkharraa, M., et al. (2023) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.033844 · Cited by 21 · see citing works

Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification

Czarnowski, I., & Jędrzejowicz, P. (2021) · IEEE Access · doi:10.1109/access.2021.3125622 · Cited by 6 · see citing works

Utilization of Big Data Analytics for Risk Management

Santhikumar, R., Kartillkayani, K., Mishra, M. K., Thota, S., Beschi, I. S., & Mishra, B. (2022) · International Conference on Inventive Research in Computing Applications (ICIRCA) · doi:10.1109/icirca54612.2022.9985709 · Cited by 5 · see citing works

Towards the Development of a Data Science Modular Solution

Fernandes, G., Portela, F., & Santos, M. F. (2019) · International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) · doi:10.1109/ficloudw.2019.00030 · Cited by 5 · see citing works

A methodological framework proposal for managing risk in small-scale farming through the integration of knowledge and data analytics

Olaya, J. F. C., & Corrales, J. C. (2024) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2024.1363744 · Cited by 2 · see citing works

Scholar-Course Knowledge Graph Construction Based on Graph Database Storage

Zheng, D., Long, Y., Zhou, Z., Chen, W., Li, J., & Tang, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-92836-0_40 · Cited by 2 · see citing works

A Practical Solution to Synchronise Structured and Non-structured Repositories

Ferreira, V. D. M., Portela, F., & Santos, M. F. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-72654-6_35 · Cited by 2 · see citing works

COVID-19 EMERGENCY AID: HOW THE BRAZILIAN GOVERNMENT USED SOCIAL BIG DATA ANALYTICS TO GIVE ECONOMIC SUPPORT AND PROTECT VULNERABLE CITIZENS

Ronqui, R. M., Oliveira, T. C. D. S., Silva, A. L. B. D., Brandão, C. E., Silva, R. R. D., Helouani, W. B., Lara, T., & Francisco, E. D. R. (2023) · Revista Contemporânea · doi:10.56083/rcv3n8-143 · Cited by 1 · see citing works

Information Extraction Berbasis Rule Untuk Soal Ujian

Soenardjo, S. N., & Gunawan, G. (2021) · Journal of Intelligent System and Computation · doi:10.52985/insyst.v2i1.154 · Cited by 1 · see citing works

Development of Scientific-Methodological Approaches to Frame Analysis of the Effectiveness of Organizational Systems

Проничкин, С. В., Chernyshova, Y. S., Gayer, A. V., & Mamai, I. B. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-90318-3_77 · Cited by 1 · see citing works

Automating Data Quality Monitoring for Environmental Air Quality System

Altarrazi, S. M., Szydło, T., Jha, D. N., & Ranjan, R. K. (2025) · ACM Symposium on Applied Computing · doi:10.1145/3672608.3707985

Big Data Processing in the IoT-Edge-Cloud Continuum

Altarrazi, S. M., Jha, D. N., Wei, B. W., Ojha, V., Solaiman, E., Barika, M., Ranjan, R. K., & Szydło, T. (2026) · Springer handbooks · doi:10.1007/978-3-031-92372-2_16

Position Paper: Minimizing Risks in Artificial Intelligence Projects

Santos, F. P., Souza, B. M. D., & Schiezaro, M. (2026) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn69854.2026.11728545

Efficient Substructure Discovery from Large Semi-structured Data

Asai, T., Abe, K., Kawasoe, S., Arimura, H., Sakamoto, H., & Arikawa, S. (2002) · SIAM International Conference on Data Mining · doi:10.1137/1.9781611972726.10 · Cited by 372 · see citing works

Survey on Mining in Semi-Structured Data

Shettar, R., & Shobha, G. (2007) · Cited by 6 · see citing works

Mining Association Rules from Semi-Structured Data.

Maruyama, K., & Uehara, K. (2000) · Cited by 7 · see citing works

Concept-Based Search on Semi-structured Data Exploiting Mined Semantic Relations

Graupmann, J. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30192-9_4 · Cited by 1 · see citing works

Structure inferring in the semistructured data

Hu, S. (2003) · Yunnan Daxue xuebao. Shehui kexue ban