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