@inproceedings{9ff07b8b8db14176895472b00d7551de,
title = "Multi-document summarization focusing on extracting and integrating similarities and differences among documents",
abstract = "The study was to develop a method for automatic summarization of sets of related research abstracts. This summarization method focused on extracting and integrating similarities and differences among different abstracts. In the research studies which aim to look for relationships between research concepts, similarities and differences are mainly reflected through research concepts and relationships expressed in the text. Thus the summarization method extracts research concepts and relationships from each research abstract, integrates similar concepts and relationships across different abstracts, and incorporates them into new sentences to produce a summary. This paper reports the three main summarization steps - discourse parsing, concept extraction and integration, and relationship extraction and integration. Each step was evaluated by comparing the machine output against human codings.",
keywords = "Automatic text summarization, Concept clustering, Concept extraction, Relationship extraction, Relationship integration",
author = "Shiyan Ou and Khoo, {Christopher S.G.} and Goh, {Dion H.}",
year = "2007",
language = "English",
series = "International Conference Recent Advances in Natural Language Processing, RANLP",
publisher = "Association for Computational Linguistics (ACL)",
pages = "442--446",
editor = "Galia Angelova and Kalina Bontcheva and Ruslan Mitkov and Nicolas Nicolov and Nikolai Nikolov",
booktitle = "International Conference Recent Advances in Natural Language Processing, RANLP 2007 - Proceedings",
address = "United States",
note = "International Conference Recent Advances in Natural Language Processing, RANLP 2007 ; Conference date: 27-09-2007 Through 29-09-2007",
}