Event Detection (ED) aims to identify event trigger words from a given text and classify it into
an event type. Most of current methods to ED rely heavily on training instances, and almost …

Named entity recognition (NER) is one of the preprocessing stages in natural language
processing (NLP), which functions to detect and classify entities in the corpus. NER results …

Urban analysis uses new data integration with computational methods to gain insight into
urban methodologies. But the challenge is how to populate automatically from various urban …

A huge amount of texts available on the World Wide Web presents an unprecedented
opportunity for information extraction (IE). One important assumption in IE is that frequent …

Resumo Named Entity Recognition problem's objective is to automatically identify and
classify entities like persons, places, organizations, and so forth. That is an area in Natural …

The task of analyzing the spatio-temporal properties of social network objects and predicting
behavioral characteristics based on them requires the development of new methods and …

A knowledge graph (KG) represents a collection of interlinked descriptions of entities. It has
become a key focus for organising and utilising this type of data for applications. Many graph …

The integration of Inductive Logic Programming (ILP) and Bottlenose Dolphin Optimization
(BDO) in this research addresses a pressing issue in today's information-saturated …

Events are vital parts of natural language, reflecting the state changes of entities. The Event
Extraction (EE) task aims to extract event triggers (the most representative words or phrases) …

Knowledge graphs are collections of interconnected descriptions of entities (objects, events
or concepts). They provide context for the data through semantic links, providing a …