DocumentCode
3579362
Title
Clustering sentences to discover events from multiple news articles using Buckshot and Fractionation
Author
SaravanaPriya, D. ; Karthikeyan, M.
Author_Institution
Department of IT, P.A College of Engineering and Technology Coimbatore, Tamilnadu
fYear
2014
Firstpage
1
Lastpage
5
Abstract
Sentence Clustering is performed based on the key terms in sentences within a document or group of documents. A sentence may come under different topics in a single document with different word of similar meaning which will not be clustered correctly by using hierarchical clustering methods. Hierarchical clustering methods are robust. They are not very efficient as its time complexity is O (n2). To overcome this problem, K-means type algorithms are used, but it handles only few documents. A proposed algorithm uses both hierarchical and partitional clustering method alternatively. It increases the accuracy and reduces the time complexity for multiple news articles. It is applied to group the text spans from multiple news articles that refer to the same event.
Keywords
Algorithm design and analysis; Clustering algorithms; Clustering methods; Data mining; Fractionation; Partitioning algorithms; Time complexity; Hierarchical relational clustering; Sentence clustering; semantically similar sentence;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Computing Research (ICCIC), 2014 IEEE International Conference on
Print_ISBN
978-1-4799-3974-9
Type
conf
DOI
10.1109/ICCIC.2014.7238566
Filename
7238566
Link To Document