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

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.

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Publication Details

Journal
Advances in Differential Equations and Control Processes
Published
2025-04-17
DOI
https://doi.org/10.59400/adecp2343
Primary Topic
Machine Learning and ELM
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Sastry Kodanda Rama Jammalamadaka, Balakrishna Kamesh Duvvuri, Sasi Bhanu Jammalamadaka, Shahida Tasneem Shaik et al.
Advances in Differential Equations and Control Processes
Machine Learning and ELM
article

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

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

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.

Advances in Differential Equations and Control ProcessesVol. 32(2)
CMR University (IN), Koneru Lakshmaiah Education Foundation (IN)
Openalex Percentile: Top 97%
Machine Learning and ELM
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