@article{2835,
  author = {Ramya C},
  title = {A Novel PSO Methodology for Web Documents Retrieval},
  journal = {International Journal of Computational Linguistics Research},
  year = {2019},
  volume = {10},
  number = {3},
  doi = {https://doi.org/10.6025/jcl/2019/10/3/67-75},
  url = {http://www.dline.info/jcl/fulltext/v10n3/jclv10n3_1.pdf},
  abstract = {This paper focuses on retrieval of web documents with improved response time and similarity using particle
swarm optimization (PSO) technique. Since the nature of the web data is distributed, volatile and uncertain, an accurate and
speedy access is required. Hence a novel approach on evolutionary bio-inspired Swarm Intelligence techniques to optimize
search process in Web Information Retrieval systems is proposed and developed. Here, we propose a novel algorithm using
basic PSO technique which works on both small CACM and huge RCV1 collections. We apply this on the pre-processed
documents to retrieve most similar documents with a very less response time. This paper also reveals a comparative study with
the existing method.},
}