AZOM: a Persian structured text summarizer

Authors:
Azadeh Zamanifar;Omid Kashefi
Affiliations:
School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran;School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Year:
2011

Citing 5
Cited 1

A maximum entropy approach to identifying sentence boundaries

ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Deep semantic interpretations of legal texts

Proceedings of the 11th international conference on Artificial intelligence and law
Hierarchical summarization of large documents

Journal of the American Society for Information Science and Technology
A New Hybrid Farsi Text Summarization Technique Based on Term Co-Occurrence and Conceptual Property of the Text

SNPD '08 Proceedings of the 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
The automatic creation of literature abstracts

IBM Journal of Research and Development

Editorial: COMPENDIUM: A text summarization system for generating abstracts of research papers

Data & Knowledge Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose a summarization approach, nicknamed AZOM, that combines statistical and conceptual property of text and in regards of document structure, extracts the summary of text. AZOM is also capable of summarizing unstructured documents. Proposed approach is localized for Persian language but easily can apply to other languages. The empirical results show comparatively superior results than common structured text summarizers, also than existing Persian text summarizers.