@article{(Open Science Index):https://publications.waset.org/pdf/10000542,
	  title     = {Automatic Enhanced Update Summary Generation System for News Documents},
	  author    = {S. V. Kogilavani and  C. S. Kanimozhiselvi and  S. Malliga},
	  country	= {},
	  institution	= {},
	  abstract     = {Fast changing knowledge systems on the Internet can
be accessed more efficiently with the help of automatic document
summarization and updating techniques. The aim of multi-document
update summary generation is to construct a summary unfolding the
mainstream of data from a collection of documents based on the
hypothesis that the user has already read a set of previous documents.
In order to provide a lot of semantic information from the documents,
deeper linguistic or semantic analysis of the source documents were
used instead of relying only on document word frequencies to select
important concepts. In order to produce a responsive summary,
meaning oriented structural analysis is needed. To address this issue,
the proposed system presents a document summarization approach
based on sentence annotation with aspects, prepositions and named
entities. Semantic element extraction strategy is used to select
important concepts from documents which are used to generate
enhanced semantic summary.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {2},
	  year      = {2015},
	  pages     = {431 - 436},
	  ee        = {https://publications.waset.org/pdf/10000542},
	  url   	= {https://publications.waset.org/vol/98},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 98, 2015},
	}