Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12358/25198
Title | Language-model-based pro/con classification of political text |
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Untitled | |
Abstract |
Given a controversial political topic, our aim is to classify documents debating the topic into pro or con. Our approach extracts topic related terms, pro/con related terms, and pairs of topic related and pro/con related terms and uses them as the basis for constructing a pro query and a con query. Following standard LM techniques, a document is classified as pro or con depending on which of the query likelihoods is higher for the document. Our experiments show that our approach is promising. |
Type | Journal Article |
Date | 2010 |
Published in | Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval |
Publisher | ACM |
Citation | |
Item link | Item Link |
License | ![]() |
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Files in this item | ||
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Language-model-based_pro_con_classificat.pdf | 298.2Kb |