Using learning and cognitive models for assessing quality of content hosted into websites

Shahida Tasneem Shaik; Hima Bindu Duddempudi; Kunal Sana; Kodanda Rama Sastry Jammalamadaka; Sasi Bhanu Jammalamadaka; Balakrishna Kamesh Duvvuri

doi:10.59400/adecp2343

Using learning and cognitive models for assessing quality of content hosted into websites

Shahida Tasneem Shaik Department of IoT, KLEF Deemed to be University, Vaddeswaram, Guntur District 522302, India
Hima Bindu Duddempudi Department of IoT, KLEF Deemed to be University, Vaddeswaram, Guntur District 522302, India
Kunal Sana Department of IoT, KLEF Deemed to be University, Vaddeswaram, Guntur District 522302, India
Kodanda Rama Sastry Jammalamadaka Department of IoT, KLEF Deemed to be University, Vaddeswaram, Guntur District 522302, India
Sasi Bhanu Jammalamadaka Department of Computer Science and Engineering, CMR College of Engineering and Technology, Hyderabad 501401, India
Balakrishna Kamesh Duvvuri Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad 500043, India

Article ID: 2343

DOI: https://doi.org/10.59400/adecp2343

Keywords: quality; assessment; computational methods; framework; WEB content; WEB sites

Abstract

The quality of a WEB site is based on 42 different factors. Out of those factors, the quality of content is the key factor. Different types of content are hosted on websites, including text, data, text data, images, videos, graphics, and animations. There are also interrelations among the content sources. The element-level connectivity and hierarchical element connectivity of content sources dictate the quality of content hosted on the website. The number of content elements, connectivity among the elements and the number of hierarchies existing on a website are many and, therefore, require a framework using which the quality of content is computed. This paper presents a framework based on an expert and ANN model. Using the framework, the quality of content hosted on a website is computed considering all sub-factors determining the quality of the factor “Content”. Using the framework proposed in this paper, the quality of the content was estimated accurately to 91.80.

Published

2025-04-17

How to Cite

Shaik, S. T., Duddempudi, H. B., Sana, K., Jammalamadaka, K. R. S., Jammalamadaka, S. B., & Duvvuri, B. K. (2025). Using learning and cognitive models for assessing quality of content hosted into websites. Advances in Differential Equations and Control Processes, 32(2), 2343. https://doi.org/10.59400/adecp2343

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Issue

Vol. 32 No. 2 (2025)

Section

Article

This work is licensed under a Creative Commons Attribution 4.0 International License.

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