Empirical Analysis of Single and Multi Document Summarization using Clustering Algorithms
Journal Title: Engineering, Technology & Applied Science Research - Year 2018, Vol 8, Issue 1
Abstract
The availability of various digital sources has created a demand for text mining mechanisms. Effective summary generation mechanisms are needed in order to utilize relevant information from often overwhelming digital data sources. In this view, this paper conducts a survey of various single as well as multi-document text summarization techniques. It also provides analysis of treating a query sentence as a common one, segmented from documents for text summarization. Experimental results show the degree of effectiveness in text summarization over different clustering algorithms.
Authors and Affiliations
M. S. Bewoor, S. H. Patil
Keywords
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