Paper: Knowledge-Based Automatic Topic Identification

ACL ID P95-1046
Title Knowledge-Based Automatic Topic Identification
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1995
Authors
  • Chin-Yew Lin (University of Southern California, Marina del Rey CA)

As the first step in an automated text sum- marization algorithm, this work presents a new method for automatically identi- fying the central ideas in a text based on a knowledge-based concept counting paradigm. To represent and generalize concepts, we use the hierarchical concept taxonomy WordNet. By setting appropri- ate cutoff values for such parameters as concept generality and child-to-parent fre- quency ratio, we control the amount and level of generality of concepts extracted from the text.