Abstract:
"
The automated text summarization is an actively researched area in NLP and several techniques
have been discovered. With the rapid growth of the data on the internet, automated
summarization has been applied to many domains. Recently online reviews have become a
very popular method that people using to express their experience and opinions on products
and services out there. With the growth of the e-business, online reviews were also increased
and became more complicated to handle. So the SumzBot approach introduced an enhanced
hybrid extractive summarization approach for review summarization with the aim of
overcoming the current accuracy in extractive summarization. The proposed system used
semantic based summarization by combining Latent Semantic Analysis (LSA) and Latent
Dirichlet Allocation (LDA) algorithms. The proposed approach has shown results that can
compete and outperform the existing systems. The Sumzbot approach was evaluated using the
ROUGE toolkit and the approach was able to achieve a high precision score compared to
existing works."
