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Authors: Liqun Shao and Jie Wang

Affiliation: University of Massachusetts, United States

Keyword(s): Title Generator, Central Sentence, Sentence Compression, Dependency Tree Pruning, TF-IDF.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Context Discovery ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: We study automatic title generation for a given block of text and present a method called DTATG to generate titles. DTATG first extracts a small number of central sentences that convey the main meanings of the text and are in a suitable structure for conversion into a title. DTATG then constructs a dependency tree for each of these sentences and removes certain branches using a Dependency Tree Compression Model we devise. We also devise a title test to determine if a sentence can be used as a title. If a trimmed sentence passes the title test, then it becomes a title candidate. DTATG selects the title candidate with the highest ranking score as the final title. Our experiments showed that DTATG can generate adequate titles. We also showed that DTATG-generated titles have higher F1 scores than those generated by the previous methods.

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Paper citation in several formats:
Shao, L. and Wang, J. (2016). DTATG: An Automatic Title Generator based on Dependency Trees. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 166-173. DOI: 10.5220/0006035101660173

@conference{kdir16,
author={Liqun Shao and Jie Wang},
title={DTATG: An Automatic Title Generator based on Dependency Trees},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR},
year={2016},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006035101660173},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR
TI - DTATG: An Automatic Title Generator based on Dependency Trees
SN - 978-989-758-203-5
IS - 2184-3228
AU - Shao, L.
AU - Wang, J.
PY - 2016
SP - 166
EP - 173
DO - 10.5220/0006035101660173
PB - SciTePress