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Knowledge Mining: A Cross-disciplinary Survey

Machine Intelligence Research volume 19, pages 89–114 (2022)Cite this article

Abstract

Knowledge mining is a widely active research area across disciplines such as natural language processing (NLP), data mining (DM), and machine learning (ML). The overall objective of extracting knowledge from data source is to create a structured representation that allows researchers to better understand such data and operate upon it to build applications. Each mentioned discipline has come up with an ample body of research, proposing different methods that can be applied to different data types. A significant number of surveys have been carried out to summarize research works in each discipline. However, no survey has presented a cross-disciplinary review where traits from different fields were exposed to further stimulate research ideas and to try to build bridges among these fields. In this work, we present such a survey.

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Authors and Affiliations

  1. Lenovo Research, Beijing, 100094, China

    Yong Rui, Vicente Ivan Sanchez Carmona, Mohsen Pourvali, Yun Xing, Wei-Wen Yi, Hui-Bin Ruan & Yu Zhang

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  1. Yong Rui
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Colored figures are available in the online version at https://link.springer.com/journal/11633

Yong Rui received the B. Sc. degree in electrical engineering from Southeast University, China in 1991, the M. Sc. degree in electrical engineering from Tsinghua University, China in 1994, and the Ph. D. degree in electrical and computer engineering from University of Illinois at Urbana-Champaign (UIUC), USA in 1999. He is currently the Chief Technology Officer and Senior Vice President of Lenovo Group, China. He is a Fellow of ACM, IEEE, IAPR, China SPIE, CCF and CAAI, and a Foreign Member of Academia Europaea. He holds 70 patents, and is the recipient of the prestigious 2018 ACM SIGMM Technical Achievement Award and 2016 IEEE Computer Society Edward J. McCluskey Technical Achievement Award.

His research interests include multimedia, artificial intelligence, big data and knowledge mining.

Vicente Ivan Sanchez Carmona received the B. Eng. and M. Eng. degree in computer engineering from National Autonomous University of Mexico, Mexico in 2008 and 2011, and the Ph. D. degree in computer science from University College London, UK in 2018. He is currently a researcher in Lenovo’s AI Lab, China. He has served as a reviewer in different conferences such as AAAI, ACL, CoNLL, COLING, among others.

His research interests include artificial intelligence, behavioral science, cognitive science and human-computer interaction.

Mohsen Pourvali received the Ph. D. degree in computer science from Ca′ Foscari University of Venice, ltaly in 2017. During the Ph. D. period, he was working on text summarization and document enrichment. Currently, he is an advisory researcher at AI Lab in Lenovo. He is an experienced lecturer with a demonstrated history of teaching in universities.

His research interests include explainable artificial intelligence and knowledge graph, especially in domain adaptive information extraction.

Yun Xing received the B. Sc. degree in optical information science and technology from Beijing Institute of Technology, China in 2012, and the M. Eng. degree in electronics and optics from Polytech Orleans, France in 2016. Currently, he is a NLP researcher in AI Lab at Lenovo Research, China.

His research interests include natural language processing in machine learning and deep learning.

Wei-Wen Yi received the B. Eng. and M. Eng. degrees in information and communication engineering from Beijing University of Posts and Telecommunications, China in 2017 and 2020, respectively. Currently, she is a natural language processing researcher at Lenovo Research, China. She received the Best Paper Award of the EAI International Conference on Communications and Networking in China, China in 2018. She is a member of EAI and IEEE.

Her research interests include named entity recognition, relation extraction and entity linking.

Hui-Bin Ruan received the M. Sc. degrees in computer technology from Soochow University, China in 2020. Currently, she is a researcher in natural language process in Lenovo, China.

Her research interests include discourse parsing, text classification and entity linking.

Yu Zhang received the B. Eng. degree in human factors, B. Sc. (Minor) degree in applied mathematics and M. Sc. degree in engineering physics from Beihang University, China in 2008, 2008 and 2011. He is currently the technical assistant to chief technology officer at Lenovo, China, and a Ph. D. degree candidate in computer science at Southeast University, China.

His research interests include human computer interaction and human-centered AI.

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Rui, Y., Carmona, V.I.S., Pourvali, M. et al. Knowledge Mining: A Cross-disciplinary Survey. Mach. Intell. Res. 19, 89–114 (2022). https://doi.org/10.1007/s11633-022-1323-6

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Keywords

  • Knowledge mining
  • knowledge extraction
  • information extraction
  • association rule
  • interpretability