TY  - JOUR
T1  - Evaluation of Multi Document Summarization Techniques
AU - Nedunchelian, R. AU - Muthucumarasamy, R. AU - Saranathan, E. 
JO  - Research Journal of Applied Sciences
VL  - 7
IS  - 4
SP  - 229
EP  - 233
PY  - 2012
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2012.229.233
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2012.229.233
KW  - Timestamp
KW  -frequent document
KW  -compression rate
KW  -comprehensibility
KW  -readability
KW  -length of summary
AB  - Multi Document Summarization is carried out using MEAD extraction algorithm, Naive Bayesian classifier and genetic algorithm. The summary generated contains the selected sentences from each document and output them in the order prevalent in the original document, the order of the sentences in the summary may not be logical in occurrence. Hence to overcome this Timestamp concept is implemented. This gives the summary an ordered look, bringing out a coherent looking summary. Instead of taking up each sentence for comparison for summarization from all documents, it would be more than enough to summarize only the document (frequent document) which has been put to many numbers of readers. The Timestamp and Frequent document concepts are used to generate multi document summarization using MEAD extraction algorithm Naive Bayesian classifier and genetic algorithm and the results are compared and evaluated.
ER  -