Name
Title | ||
|---|---|---|
Combining hierarchical clustering and machine learning to predict high-level discourse structure |
Abstract | ||
|---|---|---|
We propose a novel method to predict the interparagraph discourse structure of text, i.e. to infer which paragraphs are related to each other and form larger segments on a higher level. Our method combines a clustering algorithm with a model of segment "relatedness" acquired in a machine learning step. The model integrates information from a variety of sources, such as word co-occurrence, lexical chains, cue phrases, punctuation, and tense. Our method outperforms an approach that relies on word co-occurrence alone. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.3115/1220355.1220362 | COLING |
Keywords | Field | DocType |
higher level,larger segment,novel method,high-level discourse structure,cue phrase,hierarchical clustering,lexical chain,interparagraph discourse structure,clustering algorithm,word co-occurrence | Hierarchical clustering,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Natural language processing,Cluster analysis,Punctuation,Machine learning,Discourse structure | Conference |
Volume | Citations | PageRank |
C04-1 | 7 | 0.67 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Caroline Sporleder | 1 | 453 | 31.84 |
| alex lascarides | 2 | 503 | 68.41 |