DocumentCode
2921362
Title
Conceptual summarization using ontologies and nearest neighborhood clustering
Author
Gavagsaz, Elahe ; Naghibzadeh, Mahmoud ; Jalali, Mehrdad
Author_Institution
Dept. of Software Eng., Islamic Azad Univ., Mashhad, Iran
fYear
2011
fDate
28-29 June 2011
Firstpage
1
Lastpage
6
Abstract
Conceptual summarization aims to provide a database which comprises an abstraction of the entire document content. To effectively provide conceptual summarization, we have presented an approach that is used for conceptual querying. The approach is based on utilizing an ontology for similarity measure between concepts and the nearest neighborhood clustering algorithm for concepts clustering. The results show an improvement in the runtime and tolerant as regards noise.
Keywords
document handling; ontologies (artificial intelligence); pattern clustering; query processing; conceptual querying; conceptual summarization; document content; nearest neighborhood clustering; ontology; similarity measure; Classification algorithms; Clustering algorithms; Clustering methods; Noise; Ontologies; Semantics; Software algorithms; conceptual summarization; nearest neighborhood clustering; ontology;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Technology and Information Retrieval (STAIR), 2011 International Conference on
Conference_Location
Putrajaya
Print_ISBN
978-1-61284-354-4
Electronic_ISBN
978-1-61284-353-7
Type
conf
DOI
10.1109/STAIR.2011.5995756
Filename
5995756
Link To Document