Spectrum analysis systems in online water quality testing are designed t...
Precisely recommending candidate news articles to users has always been ...
News recommender systems (NRS) have been widely applied for online news
...
In recent years, many recommender systems have utilized textual data for...
There have been growing concerns regarding the out-of-domain generalizat...
The financial domain has proven to be a fertile source of challenging ma...
Many recent deep learning-based solutions have widely adopted the
attent...
Financial forecasting has been an important and active area of machine
l...
Leveraging unlabelled data through weak or distant supervision is a
comp...
Forecasting stock returns is a challenging problem due to the highly
sto...
While state-of-the-art NLP models have been achieving the excellent
perf...
The explosion in the sheer magnitude and complexity of financial news da...
Multi-label text classification (MLTC) is an attractive and challenging ...
Corporate mergers and acquisitions (M A) account for billions of dolla...
It has been shown that financial news leads to the fluctuation of stock
...