Text Summary using Modified Particle Swarm Optimization Algorithm

Authors

  • V. S. Raj Kumar
  • R. Danu
  • S. Shanmugapriya
  • R. Vinod

Keywords:

Differential Evolution Algorithm, Modified Particle Swarm Optimization Algorithm

Abstract

Text summarization is the process of provides meaningful and short contents of the documents in the automated manner by using which concept of entire documents can be found. In the existing work, an approach called as unsupervised generic summary creation is introduced to summarize the single document and as well as multiple documents in the generic manner. However, the genetic algorithm will consume more computational time for generating the summaries in case of presence of multiple documents with more sentences. This problem is resolved in the proposed approach by introducing the modified particle swarm optimization where global best would be updated based on weighted mean approach. This proposed approach provides an efficient and flexible creation of summaries with reduced computation time. The experimental tests conducted were proves that the proposed approach provides better result than the existing approach in terms of reduced computational time.

References

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Published

2017-01-08

How to Cite

Raj Kumar, V. S., Danu, R., Shanmugapriya, S., & Vinod, R. (2017). Text Summary using Modified Particle Swarm Optimization Algorithm. Asian Journal of Applied Sciences, 4(6). Retrieved from https://www.ajouronline.com/index.php/AJAS/article/view/4360

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