Efficient key hash indexing scheme with page rank for category based search engine big data

Ragavan, N

doi:10.1109/itcosp.2017.8303118

Cited by 3 publications

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Twitter that is ready for use, where the data has been pre-processed previously [19], where pre-processing follows from the purpose of this study. ii) The preprocessing data is then ranked by word [23], where the assumption is that the word with repeated frequency is a word that refers to the habits of Twitter social media users. iii) The results of this ranking will be checked by the campus that has been prepared, normally checking is done using string matching.…”

Section: Architecture Researchmentioning

confidence: 99%

A new approach to achieve the users’ habitual opportunities on social media

Lubis

Jaszczur²,

Sitompul³

et al. 2023

IJ-AI

View full text Add to dashboard Buy / Rent full text

<span lang="EN-US">The data generated from social media is very large, while the use of data from social media has not been fully utilized to become new knowledge. One of the things that can become new knowledge is user habits on social media. Searching for user habits on Twitter by using user tweets can be done by using modeling, the use of modeling lies when the data has been preprocessed, and the ranking will then be checked in the dictionary, this is where the role of the model is carried out to get a chance that the words that have been ranked will perform check the word in the dictionary. The benefit of the model in general is to get an understanding of the mechanism in the problem so that it can predict events that will arise from a phenomenon which in this case is user habits. So that with the availability of this model, it can be a model in getting opportunities for user habits on Twitter social media.</span>

show abstract

Section: Architecture Researchmentioning

confidence: 99%

A new approach to achieve the users’ habitual opportunities on social media

Lubis

Jaszczur²,

Sitompul³

et al. 2023

IJ-AI

View full text Add to dashboard Buy / Rent full text

show abstract

“…Big data provide a better solution to handle the hug amount of data. (Ragavan N 2017) proposed big data search engine indexing through Key Has indexing to increase the page rank in search results. The competition between site to ger first rank on search engine result is increasing day by day.…”

Section: Literature Workmentioning

confidence: 99%

Untitled

Supplemental Information 7: Trafic_overview

View full text Add to dashboard Buy / Rent full text

In search engine optimization individual website pages are optimized through precise keywords, while the websites are optimized using back link watch. The existing literature has no proper guideline for keywords selection and back link generation. In this research, we proposed a model for making back link watch generation and the selection of keywords through precise research analysis. The information on webpages consist of specific keywords while the website traffic is monitored through referrals. we concluded that during the development of Page Content, and architecture, if selected keywords are used in Title, Headings and Meta Tag then the page result is higher in search results. Moreover, for the back-link generation use a shorter volume of URL that monitor the complete traffic of a site can be placed on trusted location which increase the ranks of a site. Proposed model has been validated by comparing quantitative data of website rank taken before and after implementation of framework. Results revealed that overall increase gained in site rank by applying the proposed model was 40%.

show abstract

Efficient key hash indexing scheme with page rank for category based search engine big data

Cited by 3 publications

References 2 publications

A new approach to achieve the users’ habitual opportunities on social media

A new approach to achieve the users’ habitual opportunities on social media

Untitled

Contact Info

Product

Resources

About