@inproceedings{e4736df340094538b6d35ebccdf4a8d1,
title = "Learning Chinese polarity lexicons by integration of graph models and morphological features",
abstract = "This paper presents a novel way to learn Chinese polarity lexicons by using both external relations and internal formation of Chinese words, i.e. by integrating two kinds of different but complementary models: graph models and morphological feature-based models. The polarity detection is first treated as a semi-supervised learning in a graph, and then machine learning is used based on morphological features of Chinese words. The results show that the the integration of morphological feature-based models and graph models significantly outperforms the baselines.",
keywords = "Chinese Morphology, Graph Models, Polarity Lexicon Induction",
author = "Bin Lu and Yan Song and Xing Zhang and Tsou, \{Benjamin K.\}",
year = "2010",
doi = "10.1007/978-3-642-17187-1\_45",
language = "English",
isbn = "3642171869",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "466--477",
booktitle = "Information Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings",
note = "6th Asia Information Retrieval Societies Conference, AIRS 2010 ; Conference date: 01-12-2010 Through 03-12-2010",
}