Corpulyzer: A Novel Framework for Building Low Resource Language Corpora

Tahir, Bilal; Mehmood, Muhammad Amir

doi:10.1109/access.2021.3049793

Cited by 6 publications

(1 citation statement)

References 54 publications

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“…The work carried out by Serrano [50] has investigated the impact of deep learning for computing the learning relevance towards searching voluminous web-content. It is to be noted that a structured corpora is required for building effective SEO as noted in work of Tahir et al [51]. The work carried out by Yuan et al [52] have used a supervised learning approach for feature normalization in order to improvise the interaction process of web contents.…”

Section: Review Of Seo Approaches Using MLmentioning

confidence: 99%

Insights into Search Engine Optimization using Natural Language Processing and Machine Learning

Vinutha¹,

Padma²

2023

IJACSA

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Among the potential tools in digital marketing, Search Engine Optimization (SEO) facilitates the use of appropriate data by providing appropriate results according to the search priority of the user. Various research-based approaches have been developed to improve the optimization performance of search engines over the past decade; however, it is still unclear what the strengths and weaknesses of these methods are. As a result of the increased proliferation of Machine Learning (ML) and Natural Language Processing (NLP) in complex content management, there is potential to achieve successful SEO results. Therefore, the purpose of this paper is to contribute towards performing an exhaustive study on the respective NLP and ML methodologies to explore their strengths and weaknesses. Additionally, the paper highlights distinct learning outcomes and a specific research gap intended to assist future research work with a guideline necessary for optimizing search engine performance.

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Section: Review Of Seo Approaches Using MLmentioning

confidence: 99%