Networks and Natural Language Processing
Dragomir Radev, Rada F. Mihalcea · AI Magazine · 2008
Over the last few years, a number of areas of natural language processing have begun applying graph‐based techniques. These include, among others, text summarization, syntactic parsing, word‐sense disambiguation, ontology construction, sentiment and subjectivity analysis, and text clustering. In this paper, we present some of the most successful graph‐based representations and algorithms used in language processing and try to explain how and why they work.