@inproceedings{754770580260422691696f98061862da,
title = "Subtopic segmentation of Chinese document: An adapted dotplot approach",
abstract = "An adapted dotplot model based on Chinese word sense quantization is presented to find the boundaries of subtopics in a document The data reduction techniques of rough set are introduced for the purpose of selecting axis words for word space. To discrete and filter data in information table, mutual information between axis words and feature words is calculated. Then the adapted model is constructed through the replacing of counting identical words with calculating of sense similarity between feature words. As a submodule of our Chinese auto-summarization system {"}InsunAbs{"}, its performance is indirectly evaluated through the quantitatively evaluation of {"}InsunAbs{"}. By compared with the baseline and the original dotplot model, the performance of this adapted model is outperforming in testing experiments.",
keywords = "Attribute reduction, Dotplot, Mutual information, Rough set, Subtopic segmentation",
author = "Chen, \{Qing Cai\} and Wang, \{Xiao Long\} and Liu, \{Bing Quan\} and Wang, \{Ying Yu\}",
year = "2002",
language = "英语",
isbn = "0780375084",
series = "Proceedings of 2002 International Conference on Machine Learning and Cybernetics",
pages = "1571--1576",
booktitle = "Proceedings of 2002 International Conference on Machine Learning and Cybernetics",
note = "Proceedings of 2002 International Conference on Machine Learning and Cybernetics ; Conference date: 04-11-2002 Through 05-11-2002",
}