E-commerce Website Ranking Using Semantic Web Mining and Neural Computing

Verma, Neha; Malhotra, Dheeraj; Malhotra, Monica; Singh, Jatinder

doi:10.1016/j.procs.2015.03.080

Cited by 25 publications

(6 citation statements)

References 12 publications

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“…In another study search engine, keywords were used for the products that were sold an e-commerce firmware (21). These rankings were then evaluated by a structural algorithm called a web dictionary, in which the frequency of that word usage was measured.…”

Section: Literature Reviewmentioning

confidence: 99%

Fischer Linear Discrimination and Quadratic Discrimination Analysis–Based Data Mining Technique for Internet of Things Framework for Healthcare

Hasan

Ghazal

Alkhalifah

et al. 2021

Front. Public Health

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The internet of reality or augmented reality has been considered a breakthrough and an outstanding critical mutation with an emphasis on data mining leading to dismantling of some of its assumptions among several of its stakeholders. In this work, we study the pillars of these technologies connected to web usage as the Internet of things (IoT) system's healthcare infrastructure. We used several data mining techniques to evaluate the online advertisement data set, which can be categorized as high dimensional with 1,553 attributes, and the imbalanced data set, which automatically simulates an IoT discrimination problem. The proposed methodology applies Fischer linear discrimination analysis (FLDA) and quadratic discrimination analysis (QDA) within random projection (RP) filters to compare our runtime and accuracy with support vector machine (SVM), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) in IoT-based systems. Finally, the impact on number of projections was practically experimented, and the sensitivity of both FLDA and QDA with regard to precision and runtime was found to be challenging. The modeling results show not only improved accuracy, but also runtime improvements. When compared with SVM, KNN, and MLP in QDA and FLDA, runtime shortens by 20 times in our chosen data set simulated for a healthcare framework. The RP filtering in the preprocessing stage of the attribute selection, fulfilling the model's runtime, is a standpoint in the IoT industry.Index Terms: Data Mining, Random Projection, Fischer Linear Discriminant Analysis, Online Advertisement Dataset, Quadratic Discriminant Analysis, Feature Selection, Internet of Things.

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Section: Literature Reviewmentioning

confidence: 99%

Fischer Linear Discrimination and Quadratic Discrimination Analysis–Based Data Mining Technique for Internet of Things Framework for Healthcare

Hasan

Ghazal

Alkhalifah

et al. 2021

Front. Public Health

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“…The parameters considered for this categorization in Table 2 are as follows: 3. Research and Development: Big data analytics and IoT being a goldmine of research and development [16], it would be beneficial for new generation of researchers to further dive into new developments for future. Furthermore, it would open up vast opportunities for the next generation of mental health.…”

Section: Comparative Analysismentioning

confidence: 99%

INDUSTRY 4.0: A Comprehensive Review of Artificial Intelligence, Machine Learning, Big Data and IoT in Psychiatric Health Care

Panwar¹,

Malhotra²,

Malhotra³

2021

Lecture Notes in Networks and Systems

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It has been quite well known that modern psychiatric treatments bring along certain side effects and current treatment models are unable to precisely address the complexity of mental illness issues. As a result, there has been a major focus to search and adopt applications of information and communication technology (ICT) as a mode for some additional psychological treatment and alternative diagnose with the help of various technologies. Therefore, the objective of this study is to analyze the technological aspects of using virtual reality, artificial intelligence, machine learning, IoT and big data analytics in the mental healthcare industry. In this review paper, we have accumulated some of the remarkable studies and done a comprehensive analysis of various potential technologies in the field of psychiatric health care and the need for these technologies for improving the quality and accuracy of diagnosis for the patients.

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“…[1]have created an algorithm named the "SNEC page ranking algorithm" which is the. semantic and neural based e-commerce page ranking algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

E-Commerce Grading Approaches of Ultimate Ranking System- A Review

Kaur¹,

Bhatia²

2016

IJCA

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The e-commerce ranking algorithms are the algorithms utilized for the purpose of product suggestions and product listings against the input query or the browsed product on the given shopping portal. The product ranking portals requires the number of computations on the basis of various factors for the calculation of the ranks of the given products. Various local and online factors can be grouped for the overall evaluation of the product ranks according to the input keywords specifically on the first stage product lookup on the shopping sites. In this paper, the product ranking solution has been proposed with the versatile approach using the popularity and accessibility factors. Also the reliability factors are evaluated which analyzes the trust factor for the page by using the online security evaluation programs. Various experiments would be conducted over the large number of input product data obtained from the application programming interfaces (API) from the prominent shopping portals active online. The proposed model is expected to resolve the issue by evaluating the proposed model performance in comparison with the existing model on the basis of various factor associated with the time complexity and reliability.

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E-commerce Website Ranking Using Semantic Web Mining and Neural Computing

Cited by 25 publications

References 12 publications

Fischer Linear Discrimination and Quadratic Discrimination Analysis–Based Data Mining Technique for Internet of Things Framework for Healthcare

Fischer Linear Discrimination and Quadratic Discrimination Analysis–Based Data Mining Technique for Internet of Things Framework for Healthcare

INDUSTRY 4.0: A Comprehensive Review of Artificial Intelligence, Machine Learning, Big Data and IoT in Psychiatric Health Care

E-Commerce Grading Approaches of Ultimate Ranking System- A Review

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