Hotspot Detection and Trend Analysis in the Field of Power Measurement and Data Acquisition

In this paper, we study the research hotspot detection problem in the field of power measurement and data acquisition by using a big data and naural language processing based method. We make a combination of the TF-IDF-based and the TextRank-based keyword extraction techniques for preliminary hotspot detection, and further uses the word2vec model to merge synonyms to get more accurate detection result. By applying this method to literature in the field of power measurement and data acquisition, we obtain the annual research hotspots of this field for the past decade. Furthermore, the evolution trend analysis of hotspots is performed. The results can provide reference for practitioners in the field.

Power measurement and data acquisition, research hotspot, evolution trend, keyword and keyphrase extraction, synonym identification

Xiong Li, Jiahong Jin, Shaocheng Liao, Min Yu, Lei Han, Ziyan Chen, Hotspot Detection and Trend Analysis in the Field of Power Measurement and Data Acquisition. 2019 Scientific Conference on Network, Power Systems and Computing (NPSC 2019), 2019: 170-174. DOI: https://doi.org/10.33969/EECS.V3.039.