Graph structures in NLP
NLP has seen significant advancements in recent years, with graph-based approaches emerging as a powerful paradigm for representing and processing linguistic information. In this section, we introduce the concept of graph structures in NLP, highlighting their importance and exploring various types of linguistic graphs.
Importance of graph representations in language
Graph representations play a crucial role in capturing the inherent structure and relationships within language. They offer several advantages over traditional sequential or bag-of-word modeling, which is a simple text representation technique that converts a document into a vector by counting the frequency of each word, disregarding grammar and word order:
- Structural information: Graphs can explicitly represent the hierarchical and relational nature of language, preserving important linguistic structures that may be lost in linear representations.
- Contextual relationships: By connecting...
