Paper: Text Summarization through Entailment-based Minimum Vertex Cover

ACL ID S14-1010
Title Text Summarization through Entailment-based Minimum Vertex Cover
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

Sentence Connectivity is a textual charac- teristic that may be incorporated intelli- gently for the selection of sentences of a well meaning summary. However, the ex- isting summarization methods do not uti- lize its potential fully. The present pa- per introduces a novel method for single- document text summarization. It poses the text summarization task as an opti- mization problem, and attempts to solve it using Weighted Minimum Vertex Cover (WMVC), a graph-based algorithm. Tex- tual entailment, an established indicator of semantic relationships between text units, is used to measure sentence connectivity and construct the graph on which WMVC operates. Experiments on a standard sum- marization dataset show that the suggested algorithm outperforms related methods.