Abstract
To manage the huge information, summarization is one of the most essential tasks. There are many techniques available for this purpose, yet this is a challenge to produce the optimum solution. This paper proposes an approach for text summarization based on sentiment analysis and cuckoo search algorithm. For solving the optimization problem in several areas, the cuckoo search algorithm is used. The cuckoo search basically is a type of nature-inspired algorithms. It is efficient for solving the global optimization problem as it is capable to proceed by maintaining balance between local and global random walks. Here we use cuckoo search algorithm with sentiment score for summarizing the text document. The experimental analysis uses benchmark database. The outcome of the proposed model has been compared in terms of ROUGE score with some existing and some human-generated output.
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Mandal, S., Singh, G.K., Pal, A. (2020). Text Summarization Technique by Sentiment Analysis and Cuckoo Search Algorithm. In: Iyer, B., Deshpande, P., Sharma, S., Shiurkar, U. (eds) Computing in Engineering and Technology. Advances in Intelligent Systems and Computing, vol 1025. Springer, Singapore. https://doi.org/10.1007/978-981-32-9515-5_34
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DOI: https://doi.org/10.1007/978-981-32-9515-5_34
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