DocumentCode :
3317993
Title :
Multilingual single document keyword extraction for information retrieval
Author :
Bracewell, David B. ; Ren, Fuji ; Kuriowa, Shingo
Author_Institution :
Dept. of Inf. Sci. & Intelligent Syst., Tokushima Univ., Japan
fYear :
2005
fDate :
30 Oct.-1 Nov. 2005
Firstpage :
517
Lastpage :
522
Abstract :
Keywords play an important role in many aspects of information retrieval (IR). From Web searches to text summarization good keywords are a necessity. In a typical IR system algorithms are used which require the entire document collection to be built beforehand. While some research has been done on extracting keywords from a single document, the quality of the keywords was not based on how well they perform in IR tasks. Moreover, they are designed for only one language and the applicability to other languages is unknown. As such, this paper proposes a new algorithm that is applicable to multiple languages and extracts effective keywords that, to a high degree, uniquely identify a document. It needs only a single document to extract keywords and does not rely on machine learning methods. It was tested on a Japanese-English bilingual corpus and a portion of the Reuter´s corpus using a keyword search algorithm. The results show that the extracted keywords do a good job at uniquely identifying the documents.
Keywords :
information retrieval; linguistics; natural languages; IR; Japanese-English bilingual corpus; Reuter corpus; information retrieval; keyword search algorithm; multilingual single document keyword extraction; Algorithm design and analysis; Data mining; Humans; Information retrieval; Information science; Keyword search; Machine learning algorithms; Natural languages; Testing; Web search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on
Print_ISBN :
0-7803-9361-9
Type :
conf
DOI :
10.1109/NLPKE.2005.1598792
Filename :
1598792
Link To Document :
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