@inproceedings{bdae0c83058442caa9ab1b00e26eca39,
title = "An improved discriminative category matching in relation identification",
abstract = "This paper describes an improved method for relation identification, which is the last step of unsupervised relation extraction. Similar entity pairs maybe grouped into the same cluster. It is also important to select a key word to describe the relation accurately. Therefore, an improved DF feature selection method is employed to rearrange low-frequency entity pairs' features in order to get a feature set for each cluster. Then we used an improved Discriminative Category Matching (DCM) method to select typical and discriminative words for entity pairs' relation. Our experimental results show that Improved DCM method is better than the original DCM method in relation identification.",
keywords = "Improved DCM, Improved DF, Low-frequency entity pair, Unsupervised Relation Extraction",
author = "Yongliang Sun and Jing Yang and Xin Lin",
year = "2013",
doi = "10.1007/978-3-642-38824-8\_39",
language = "英语",
isbn = "9783642388231",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "363--366",
booktitle = "Natural Language Processing and Information Systems - 18th International Conference on Applications of Natural Language to Information Systems, NLDB 2013, Proceedings",
note = "18th International Conference on Application of Natural Language to Information Systems, NLDB 2013 ; Conference date: 19-06-2013 Through 21-06-2013",
}