The text records of urban rail transit operation emergencies contain information about the
relationship between events, which can provide auxiliary support for emergency decision …

The deep learning has become an important technique for semantic relation classification in
patent texts. Previous studies just borrowed the relevant models from generic texts to patent …

Determining a technology's potential applications is crucial in assessing its level of
innovation and evaluating its commercial viability. However, patent documents offer limited …

Text analysis on technology has recently been progressing from the level of words to
semantic relations between words. However, existing research methods, such as Subject …

Quality problem-solving (QPS) is one of the most important processes to ensure product
quality. In the context of Industry 4.0, increasingly more manufacturing companies have …

Discovering technology opportunities from the opinion of users can promote successful
technological development by satisfying the needs of users. However, although previous …

Patent data contain plenty of valuable information. Recently, the lack of innovative ideas has
resulted in some enterprises encountering bottlenecks in product research and development …

With the advent of the knowledge economy, firms often compete for intellectual property
rights. Being the first to acquire high-potential patents can assist firms in achieving future …

Extracting causal relations between events from text is vital in natural language processing.
Existing methods, which explore the text shallowly, usually aim at casual connection words …

Event causality identification (ECI) aims to identify causal relations between events in texts.
Although existing event causality identification works based on fine-tuning pre-trained …