Effects of central tendency measures on term weighting in textual information retrieval

Ghahramani, Farzad; Tahayori, Hooman; Visconti, Andrea

doi:10.1007/s00500-021-05694-5

Cited by 4 publications

(2 citation statements)

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“…[1] It also looks at the most recent studies on how to incorporate user behaviour and interests into page rank algorithms to improve page rank algorithms. [2] Utilizing the suggested technique on various datasets, Average, median, and mid-range are a subset of basic weighting methods that produce more efficient weights when compared to the recently introduced sophisticated weighting methods. [3] Classifiers were created and trained in this research to categorise an unknown sample (web page of page adjustment).…”

Section: Literature Surveymentioning

confidence: 99%

“…The relevance calculator estimates a page's relevance on the fly based on two factors: one shows the likelihood that the query will be answered in the page, and the other represents the query's maximum match to the page. Reference [2] The weighted web page rank approach assigns higher page rank ranks to more significant (popular) websites. The number of inbound and outgoing links on a website determines its popularity, and each website is assigned a proportional web page rank grade.…”

Section: Relevancy Calculatormentioning

confidence: 99%

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Weighted PageRank Algorithm Search Engine Ranking Model for Web Pages

Shaffi¹,

Muthulakshmi²

2023

Intelligent Automation &Amp; Soft Computing

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As data grows in size, search engines face new challenges in extracting more relevant content for users' searches. As a result, a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user's requirements. Unfortunately, most existing indexes and ranking algorithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations, making it impossible to deliver exceptionally accurate results. As a result, this study investigates and analyses how search engines work, as well as the elements that contribute to higher ranks. This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm, which is one of the most widely used page ranking algorithms We propose weighted PageRank (WPR) algorithms to test the relationship between these various measures. The Weighted Page Rank (WPR) model was used in three distinct trials to compare the rankings of documents and pages based on one or more user preferences criteria. The findings of utilizing the Weighted Page Rank model showed that using multiple criteria to rank final pages is better than using only one, and that some criteria had a greater impact on ranking results than others.

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Section: Literature Surveymentioning

confidence: 99%

Section: Relevancy Calculatormentioning

confidence: 99%