TY - GEN
T1 - Performing literature review using text mining, Part II
T2 - 5th IEEE International Conference on Big Data, Big Data 2017
AU - Yang, Dazhi
AU - Hong, Jihoon
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - An abbreviation is often used in scientific communications when a concept is needed to be addressed repeatedly. Although some concepts can be described with a single word, e.g., mechanics, phrases are commonly required for more elaborated concepts, e.g., quantum mechanics. It is believed that by extracting abbreviations from full texts on a scientific topic could help expand the domain knowledge of a novice. A text mining algorithm is used to extract the abbreviations from 247 full texts on predictive maintenance-a manufacturing topic-hosted on ScienceDirect. It is found that the abbreviations extracted are useful for generating domain-specific dendrograms, which can provide valuable information during literature review on a scientific area. This paper is the second of a multi-part study, namely, performing literature review using text mining.
AB - An abbreviation is often used in scientific communications when a concept is needed to be addressed repeatedly. Although some concepts can be described with a single word, e.g., mechanics, phrases are commonly required for more elaborated concepts, e.g., quantum mechanics. It is believed that by extracting abbreviations from full texts on a scientific topic could help expand the domain knowledge of a novice. A text mining algorithm is used to extract the abbreviations from 247 full texts on predictive maintenance-a manufacturing topic-hosted on ScienceDirect. It is found that the abbreviations extracted are useful for generating domain-specific dendrograms, which can provide valuable information during literature review on a scientific area. This paper is the second of a multi-part study, namely, performing literature review using text mining.
KW - abbreviation extraction
KW - literature review
KW - predictive maintenance
KW - text mining
UR - https://www.scopus.com/pages/publications/85047804090
U2 - 10.1109/BigData.2017.8258314
DO - 10.1109/BigData.2017.8258314
M3 - 会议稿件
AN - SCOPUS:85047804090
T3 - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
SP - 3297
EP - 3301
BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
A2 - Nie, Jian-Yun
A2 - Obradovic, Zoran
A2 - Suzumura, Toyotaro
A2 - Ghosh, Rumi
A2 - Nambiar, Raghunath
A2 - Wang, Chonggang
A2 - Zang, Hui
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Hu, Xiaohua
A2 - Kepner, Jeremy
A2 - Cuzzocrea, Alfredo
A2 - Tang, Jian
A2 - Toyoda, Masashi
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2017 through 14 December 2017
ER -