Article Structure
Abstract
We study the global topology of the syntactic and semantic distributional similarity networks for English through the technique of spectral analysis.
Introduction
Syntax and semantics are two tightly coupled, yet very different properties of any natural language — as if one is from “Mars” and the other from “Venus”.
Network Construction
The syntactic and semantic DSNs are constructed from a raw text corpus.
Spectrum of DSNs
Spectral analysis refers to the systematic study of the eigenvalues and eigenvectors of a network.
Eigenvector Analysis
The first eigenvalue tells us to what extent the rows of the adjacency matrix are correlated and therefore, the corresponding eigenvector is not a dimension pointing to any classificatory basis of the words.
Conclusion and Future Work
Here, we presented some initial investigations into the nature of the syntactic and semantic DSNs through the method of spectral analysis, whereby we could observe that the global topology of the two networks are significantly different in terms of the organization of their natural classes.
Topics
distributional similarity
- We study the global topology of the syntactic and semantic distributional similarity networks for English through the technique of spectral analysis.Page 1, “Abstract”
- An alternative, but equally popular, visualization of distributional similarity is through graphs or networks, where each word is represented as nodes and weighted edges indicate the extent of distributional similarity between them.Page 1, “Introduction”
- intriguing question, whereby we construct the syntactic and semantic distributional similarity network (DSN) and analyze their spectrum to understand their global topology.Page 1, “Introduction”
See all papers in Proc. ACL 2009 that mention distributional similarity.
See all papers in Proc. ACL that mention distributional similarity.
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