A Prediction and Push Method of Scientific Researching Issue Based on RNN

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Ma, Yan^1 ; Qi, Dali^1 ; Yu, Naihai^2 ; Zou, Lida^3

State Grid Shandong Electric Power Research Institute, Jinan

250002, China^1

Shandong Electric Power Industrial Boiler Pressure Vessel Inspection Center, Jinan

250002, China^2

Shandong University of Finance and Economics, Jinan

250014, China^3

关键词: Academic literature;    Developing trend;    False positive;    Forward looking;    Information research;    Technical applications;    Term Frequency;    Word frequencies;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/4/042079/pdf
DOI  :  10.1088/1757-899X/452/4/042079

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Exploring and predicting the hot scientific researching issues have been a focus among recent sci-tech information research. In recent years, scholars and academic literature are increasing steadily in number. It is hard to artificially track and deal with developing trends of scientific researching hotspot. The most commonly used methods in the past are simple statistical ways for keywords and high term frequency. Most of these methods spend a lot of time and manpower, and ignore the relevance between different words. In the paper we use RNN method to design our prediction and push system, which could perceive the potential researching hotspot for some time to come. The hot issues are generated based on the relevance among sci-tech words. It finds the relevant technical application to hotspots and recommends them to academic researchers. The extensive experiments demonstrate that our proposed approach has higher accuracy rate and lower false positive ratio. It can do better forward looking forecasts than word frequency statistics as well.