Paper: Automatic Headline Generation using Character Cross-Correlation

ACL ID P11-3021
Title Automatic Headline Generation using Character Cross-Correlation
Venue Annual Meeting of the Association of Computational Linguistics
Session Student Session
Year 2011
Authors

Arabic language is a morphologically com- plex language. Affixes and clitics are regu- larly attached to stems which make direct comparison between words not practical. In this paper we propose a new automatic headline generation technique that utilizes character cross-correlation to extract best headlines and to overcome the Arabic lan- guage complex morphology. The system that uses character cross-correlation achieves ROUGE-L score of 0.19384 while the exact word matching scores only 0.17252 for the same set of documents.