DocumentCode :
2387872
Title :
Identifying citing sentences in research papers using supervised learning
Author :
Sugiyama, Kazunari ; Kumar, Tarun ; Kan, Min-Yen ; Tripathi, Ramesh C.
Author_Institution :
Dept. of Comput. Sci., Nat. Univ. of Singapore, Singapore, Singapore
fYear :
2010
fDate :
17-18 March 2010
Firstpage :
67
Lastpage :
72
Abstract :
Researchers have largely focused on analyzing citation links from one scholarly work to another. Such citing sentences are an important part of the narrative in a research article. If we can automatically identify such sentences, we can devise an editor that helps suggest when a particular piece of text needs to be backed up with a citation or not. In this paper, we propose a method for identifying citing sentences by constructing a classifier using supervised learning. Our experiments show that simple language features such as proper nouns and the labels of previous and next sentences are effective features to identifying citing sentences.
Keywords :
citation analysis; learning (artificial intelligence); pattern classification; citing sentences identification; pattern classifier; research paper; supervised learning; Bibliographies; Citation analysis; Computer science; Information analysis; Information retrieval; Information technology; Intersymbol interference; Natural languages; Software libraries; Supervised learning; citation analysis; digital library; discourse processing; information retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Retrieval & Knowledge Management, (CAMP), 2010 International Conference on
Conference_Location :
Shah Alam, Selangor
Print_ISBN :
978-1-4244-5650-5
Type :
conf
DOI :
10.1109/INFRKM.2010.5466945
Filename :
5466945
Link To Document :
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