Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

This work presents and assesses the power of various volumetric, sentiment, and social
network approaches to predict crucial decisions from online social media platforms. The …

Abstract Social Media Prediction (SMP) is an emerging powerful tool attracting the attention
of researchers and practitioners alike. Despite its many merits, SMP has also several …

This paper investigates the soybean futures price prediction problem from a new perspective
and proposes an effective prediction model named Two‐Stage Hybrid Long Short‐Term …

Knowing the prices of agricultural commodities in advance can provide governments,
farmers, and consumers with various advantages, including a clearer understanding of the …

Exploiting advanced and appropriate methods to construct high‐quality features from
different types of data becomes crucial in agricultural futures price forecasting. Thus, this …

Agricultural researchers, in common with other domains, have recently began to have
access to large collections of agricultural texts such as scientific papers and news stories …

[目的/意义] 支撑数据密集型科学发现下科技创新生态的知识服务新业态正悄然形成.
文本挖掘作为知识服务技术的核心, 在知识服务新业态环境下面临挑战. 本文旨在探讨在新环境 …

We are in a transitional economic period emphasizing automation of physical jobs and the
shift towards intellectual labor. How can we measure and understand human behaviors of …

Agricultural commodity prices fluctuations often cause losses, especially for middle to lower-
class people. Predicting future prices is essential for formulating policies for each entity …