A Comparative Study of Link Analysis Algorithms

Palihawadana, Chamath; Poravi, Guhanathan

doi:10.1109/isms.2018.00028

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…When the user enters the query, the traditional search engine (such as the Google search engine) analyzes the page links that match the query and ranks the relevant pages [10], [11]. The ranking of the page is mainly based on the voting behavior between the links [12], [13].…”

Section: A Personal Searchmentioning

confidence: 99%

A Study of Optimizing Search Engine Results Through User Interaction

Chen

2020

IEEE Access

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In this paper, we propose a method for optimizing search engine results based on user interaction. This method generates different search results mainly through the user's operation on different search topics. There are two main differences between our method and the traditional personalized search method: personal privacy and storage space. First, traditional personal search methods need to record search and click records for individual users. However, these records have great personal privacy issues for users; especially in recent years, there have been personal privacy leaks that occurred in many large online companies (such as Facebook and Yahoo). Secondly, because different users need to record their own search records, the size of the storage space is closely related to the number of users and the amount of search records stored. However, the sum of individual users' search and click records is a huge storage space in today's Internet environment. To avoid these two issues for traditional personalized search methods, this study proposes a storage-free approach based on individual users operating on different search topics. In general, in addition to avoiding personal privacy and storage space issues, our method can also achieve optimal linear time in generating personalized search results. INDEX TERMS Document clustering, machine learning, natural language processing, personalized topic search, user log.

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Section: A Personal Searchmentioning

confidence: 99%

A Study of Optimizing Search Engine Results Through User Interaction

Chen

2020

IEEE Access

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“…As the amount of knowledge available on the worldwide web increases nearly every day, the search engine's ability to deliver most appropriate material to the one who use is becoming more and more challenging, without any assistance in filtering through all of it, knowing specifically what you require may be extremely difficult. The aim of ranking algorithms is always to help you reach what you're searching for, by filtering across hundreds of millions of web sites in the data base in a couple of seconds to search its most important, usable results [3].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Search Engine Ranking Algorithms

2021

IJATCSE

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Ranking Algorithm is the most proper way of positioning on a scale. As the information and knowledge on the internet are increasing every day.The search engine's ability to deliver the most appropriate material to the customer. It is more and more challenging without even any assistance in filtering through all of it. However, searching what user requires is extremely difficult. In this research, an effort has been made to compare and analyze the most popular and effective search engines. The keywords were used in uniform resource locator like, title tag, header, or even the keyword's resembles to the actual text. The page rank algorithm computes a perfect judgment of how relevant a webpage is by analyzing the quality and calculating the number of links connected to it. In this study the keyword relevancy and time response were used for search engines and observed the results. It is observed that the google search engine is faster than the bing and youtube, and after all, bing is the best search engine after google. Moreover, youtube is the fastest search engine in terms of video content search. The google results were found more accurate. However, it is better than all of the search engine

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A Comparative Study of Link Analysis Algorithms

Cited by 2 publications

References 9 publications

A Study of Optimizing Search Engine Results Through User Interaction

A Study of Optimizing Search Engine Results Through User Interaction

A Comparative Analysis of Search Engine Ranking Algorithms

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