Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

The rapid development of data and artificial intelligence technology has introduced new
opportunities and challenges to aeronautical information intelligence. However, there are …

We describe the CoNLL-2003 shared task: language-independent named entity recognition.
We give background information on the data sets (English and German) and the evaluation …

Interested in how an efficient search engine works? Want to know what algorithms are used
to rank resulting documents in response to user requests? The authors answer these and …

We describe Web-a-Where, a system for associating geography with Web pages. Web-a-
Where locates mentions of places and determines the place each name refers to. In …

Automatic metadata generation provides scalability and usability for digital libraries and their
collections. Machine learning methods offer robust and adaptable automatic metadata …

News articles contain a wealth of implicit geographic content that if exposed to readers
improves understanding of today's news. However, most articles are not explicitly geotagged …

We apply a memory-based learner to the CoNLL-2002 shared task: language-independent
named entity recognition. We use three additional techniques for improving the base …

In this report, we explore various methods that are applied to solve NER. In section 1, we
introduce the named entity problem. In section 2, various named entity recognition methods …

STEWARD (" Spatio-Textual Extraction on the Web Aiding Retrieval of Documents"), a
system for extracting, querying, and visualizing textual references to geographic locations in …