Social media platforms are popular for expressing personal views, emotions and beliefs.
Social media platforms are influential for propagating extremist ideologies for group …

Text augmentation is a popular technique in natural language processing (NLP) that has
been shown to improve the performance of various downstream tasks. The goal of text …

Representing building layouts as graphs can extract critical design patterns that would
facilitate space syntax analyses as well as design mining and automation but traditional …

Extracting valuable insights from vast amounts of unstructured digital text presents
significant challenges across diverse domains. This research addresses this challenge by …

Natural language processing is still an emerging field in machine learning. Access to more
and more data sets in textual form, new applications for artificial intelligence and the need …

While most previous research focused only on the textual content of documents, advanced
support for document management in digital libraries, for open science, requires handling all …

The rapid development of natural language processing and deep learning techniques has
boosted the performance of related algorithms in several linguistic and text mining tasks …

Text-graph representation learning is a critical and important area of research with extensive
applications in natural language processing (NLP). Recently, graph learning models based …

Text representation is the preliminary work for in-depth analysis and mining of information in
scientific papers. It directly affects the effects of downstream tasks such as, scientific papers …

Graph pattern matching is widely used in real-world applications, such as social network
analysis. Since the traditional subgraph isomorphism is NP-complete and often too …