This paper describes a method for selecting TV news stories and newswire articles related to a target article of newswire by using a machine learning technique called SVM (Support Vector Machines) We used selected antecedents of overt pronouns, compound nouns in the experiments. The results of experiments showed that the use of antecedents of overt pronouns and compound nouns for SVM is effective. And SVM is more effective than term weighting methods such as word density, TF*IDF, χ2, a method based on entropy or a method based on standard deviation for event detection.
Cite as: Suzuki, Y., Fukumoto, F., Sekiguchi, Y. (2000) Selecting TV news stories and newswire articles related to a target article of newswire using SVM. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 2, 668-671, doi: 10.21437/ICSLP.2000-357
@inproceedings{suzuki00_icslp,
author={Yoshimi Suzuki and Fumiyo Fukumoto and Yoshihiro Sekiguchi},
title={{Selecting TV news stories and newswire articles related to a target article of newswire using SVM}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 2, 668-671},
doi={10.21437/ICSLP.2000-357}
}