典型文献
Knowledge Mining:A Cross-disciplinary Survey
文献摘要：
Knowledge mining is a widely active research area across disciplines such as natural language processing(NLP),data min-ing(DM),and machine learning(ML).The overall objective of extracting knowledge from data source is to create a structured repres-entation 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.
文献关键词：
中图分类号：
作者姓名：
Yong Rui;Vicente Ivan Sanchez Carmona;Mohsen Pourvali;Yun Xing;Wei-Wen Yi;Hui-Bin Ruan;Yu Zhang
作者机构：
Lenovo Research,Beijing 100094,China
文献出处：
引用格式：
[1]Yong Rui;Vicente Ivan Sanchez Carmona;Mohsen Pourvali;Yun Xing;Wei-Wen Yi;Hui-Bin Ruan;Yu Zhang-.Knowledge Mining:A Cross-disciplinary Survey)[J].机器智能研究（英文）,2022(02):89-114
A类：
repres
B类：
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AB值：
0.647792
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