A novel web ranking algorithm based on pages multi-attribute

Baker M. R., AKCAYOL M. A.

International Journal of Information Technology (Singapore), cilt.14, sa.2, ss.739-749, 2022 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 2
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s41870-021-00833-5
  • Dergi Adı: International Journal of Information Technology (Singapore)
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.739-749
  • Anahtar Kelimeler: Information retrieval, Meta-tag parse, Page extraction, Query analysis, Text mining, Web ranking algorithm, Word frequency
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021, Bharati Vidyapeeth's Institute of Computer Applications and Management.The size of the Internet is rapidly increasing. It has become a necessity to access information on the web correctly for a short time. For this reason, search engines have arisen out of meeting this need. In this study, we propose a ranking algorithm based on page multi-attribute (PMARank). The proposed algorithm uses a novel index calculation system that acts as a pre-rank process for web pages. In the ranking procedure, the featured meta-tag of a page and its contents were extracted to locate words as ranking features. The proposed web ranking algorithm has been compared with PageRank (PR) and Hyperlink-Induced Topic Search (HITS) algorithms. Experimental results show that the proposed ranking algorithm performs better than PR and HITS algorithms according to user clickstreams on the search results page.