Abstract: In this paper, we present a big data-based stock price prediction method to analyze market trends better. Investors and market analysts need to predict correctly as the stock market is ...

Amid rising demand for digital and technology-driven skills, Harvard University has made several of its courses accessible online at no cost through its learning platform. The offerings span key areas ...

Original Reporting This article contains firsthand information gathered by reporters. This includes directly interviewing sources and analyzing primary source documents. Subject Specialist The ...

Four years ago, a security incident sent our engineering team on a new course: After the scramble of gathering logs and getting more frustrated with the limited visibility that comes with ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

We use the stock selection benchmark dataset from https://github.com/fulifeng/Temporal_Relational_Stock_Ranking/tree/master. To prepare the data: feature_describe ...

Time-series data—measurements collected at regular intervals, like stock prices or traffic flows—has become a key driver of intelligent decision-making systems across industries. From medical ...

The sun sets over the Hudson River on a crisp fall day, casting an orange glow through the windows over the 20 or so M.S. in Sustainability Science (SUSCI) students huddled over their laptops on the ...

Abstract: High-resolution time series data are crucial for the operation and planning of energy systems such as electrical power systems and heating systems. Such data often cannot be shared due to ...

Time-series data—measurements collected over time like stock prices or heart rates—plays a vital role in AI forecasting systems across industries. As these systems advance, the need for time-series ...