After decades of massive digitisation, an unprecedented number of historical documents are
available in digital format, along with their machine-readable texts. While this represents a …

A vast amount of location information exists in unstructured texts, such as social media
posts, news stories, scientific articles, web pages, travel blogs, and historical archives …

Combining computational technologies and humanities is an ongoing effort aimed at making
resources such as texts, images, audio, video, and other artifacts digitally available …

Natural language texts, such as tweets and news, contain a vast amount of geospatial
information, which can be extracted by first recognizing toponyms in texts (toponym …

Geographic text analysis (GTA) research in the digital humanities has focused on projects
analyzing modern English-language corpora. These projects depend on temporally specific …

Understanding historical events is necessary for the study of contemporary society, culture,
and politics. In this work, we focus on the event extraction task (EE) to detect event trigger …

Information on historical flood levels can be communicated verbally, in documents, or in the
form of flood marks. The latter are the most useful from the point of view of public awareness …

Purpose By map**-out the capabilities, challenges and limitations of named-entity
recognition (NER), this article aims to synthesise the state of the art of NER in the context of …

In recent years, the Chinese tourism industry has developed rapidly, leading to significant
changes in the relationship between people and space patterns in scenic regions. To attract …

Named Entity Recognition in texts is an important natural language processing task. There
are many systems to solve this problem. These systems differ in targeting domains …