%0 Conference Paper %1 Ohsawa98KeyGraph %A Ohsawa, Yukio %A Benson, Nels E. %A Yachida, Masahiko %B ADL '98: Proceedings of the Advances in Digital Libraries Conference %C Washington, DC, USA %D 1998 %I IEEE Computer Society %K 98 KeyGraph Ohsawa co-occurrence extraction graph keyword text %P 12 %T KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor %U http://portal.acm.org/citation.cfm?id=785950 %X In this paper, we present an algorithm for extracting keywords representing the asserted main point in a document, without relying on external devices such as natural language processing tools or a document corpus. Our algorithm KeyGraph is based on the segmentation of a graph, representing the co-occurrence between terms in a document, into clusters. Each cluster corresponds to a concept on which author's idea is based, and top ranked terms by a statistic based on each term's relationship to these clusters are selected as keywords. This strategy comes from considering that a document is constructed like a building for expressing new ideas based on traditional concepts.The experimental results show that thus extracted terms match author's point quite accurately, even though KeyGraph does not use each term's average frequency in a corpus, i.e., KeyGraph is a content-sensitive, domain independent device of indexing. %@ 0-8186-8464-X

@inproceedings{Ohsawa98KeyGraph, abstract = {In this paper, we present an algorithm for extracting keywords representing the asserted main point in a document, without relying on external devices such as natural language processing tools or a document corpus. Our algorithm KeyGraph is based on the segmentation of a graph, representing the co-occurrence between terms in a document, into {\it clusters}. Each cluster corresponds to a concept on which author's idea is based, and top ranked terms by a statistic based on each term's relationship to these clusters are selected as keywords. This strategy comes from considering that a document is constructed like a building for expressing new ideas based on traditional concepts.The experimental results show that thus extracted terms match author's point quite accurately, even though KeyGraph does not use each term's average frequency in a corpus, i.e., KeyGraph is a content-sensitive, domain independent device of indexing.}, added-at = {2010-03-05T18:18:09.000+0100}, address = {Washington, DC, USA}, author = {Ohsawa, Yukio and Benson, Nels E. and Yachida, Masahiko}, biburl = {https://www.bibsonomy.org/bibtex/2f9ab6daf526414a4ab15fda68e972436/lee_peck}, booktitle = {ADL '98: Proceedings of the Advances in Digital Libraries Conference}, description = {KeyGraph}, interhash = {69c44e990b5039de46078241194d2e5c}, intrahash = {f9ab6daf526414a4ab15fda68e972436}, isbn = {0-8186-8464-X}, keywords = {98 KeyGraph Ohsawa co-occurrence extraction graph keyword text}, pages = 12, publisher = {IEEE Computer Society}, timestamp = {2010-03-05T18:18:09.000+0100}, title = {KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor}, url = {http://portal.acm.org/citation.cfm?id=785950}, year = 1998 }