Page ranking based on number of visits of links of Web page

Kumar, Gyanendra; Duhan, Neelam; Sharma, Ashok Kumar

doi:10.1109/iccct.2011.6075206

Cited by 45 publications

(21 citation statements)

References 3 publications

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“…Gyanendra Kumar and A K Sharma [7] proposed page rank based on visits of links (VOL). Page ranking algorithm is implemented based on visits of links for search engine which works on the basic ranking algorithm of Google.…”

Section: Related Workmentioning

confidence: 99%

Semantic based Re-ranking model Using WordNet for retrieving Web URL in E- learning

Ramesh¹,

Chandrasekar²

2016

IJIREM

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E-learning is fast, appropriate and just-in-time learning growth from the learning requirements of the new dynamically changing, distributed business world. Nowadays modeling user's preferences is one of the tricky tasks in elearning systems that deal with huge volumes of information. The term "Semantic Web" encompasses efforts to build a new search engine that supports content with formal semantics, which Permits better potentialities for browsing and exploring through the cyberspace. Information retrieval by searching users query on the web is not a fresh idea but has different challenges when it compared to general information retrieval. Different search engine return different search results due to variation in indexing and search process. Semantic web can solve the problem in web with semantic annotations to provide intelligent and meaningful understanding by way of making use of query interface mechanism. In this work, we present a method for using genealogical data from ontology in finding the compatible hierarchical principles for question extension, and ranking websites founded on semantic family members of the hierarchical principles related to question terms, thinking of the hierarchical members of the family of domain searched (sibling, synonyms and hyponyms) via extraordinary weighting based on Re-ranking method. So, it provides an accurate answer for ranking records when compared to the previous methods.

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Section: Related Workmentioning

confidence: 99%

Semantic based Re-ranking model Using WordNet for retrieving Web URL in E- learning

Ramesh¹,

Chandrasekar²

2016

IJIREM

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“…D=damping factor (Whose value is 0.85(approx)) In Equation (3) we can see that (1-d+d) =1 so it simply multiply 1 with the equation (1) and (2). Here d means user actually follows the link structure and (1-d) means user is randomly select any page on WWW.…”

Section: Pagerank Algorithmmentioning

confidence: 99%

“…PageRank and takes number of visits of inbound links of Web pages into account. This concept is very useful to display most valuable pages on the top of the result list on the basis of user browsing behaviour, which reduces the search space to a large scale [2].…”

Section: Search Enginementioning

confidence: 99%

PageRank algorithm and its variations: A Survey report

Kumar¹,

Mukoko²

2013

IOSR-JCE

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“…Kumar and et al proposed the PageRank algorithm based on Visits of Links (VOL) for search engines, which takes the number of visits of inbound links of web pages into account [12].…”

Section: Related Workmentioning

confidence: 99%

Presentation of an Extended Version of the PageRank Algorithm to Rank Web Pages Inspired by Ant Colony Algorithm

Setayesh¹,

Harounabadi²,

Rahmani³

2014

IJCA

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The general search engines represent various results in their lists, which is very time consuming to check. . One way to limit the search engine results is to use ranking pages algorithm in web. One of the most important ranking algorithms of web pages in the internet is known as "PageRank", which works on the web-graph structure.In this article, an extended version of the "PageRank" algorithm taking into consideration the degree of user interest in web pages and the ant colony algorithm is presented. Simulation results indicate that in the recommended algorithm ranks are closer to the real data; they produce more distinguished ranks, and have a less amount of errors.

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Page ranking based on number of visits of links of Web page

Cited by 45 publications

References 3 publications

Semantic based Re-ranking model Using WordNet for retrieving Web URL in E- learning

Semantic based Re-ranking model Using WordNet for retrieving Web URL in E- learning

PageRank algorithm and its variations: A Survey report

Presentation of an Extended Version of the PageRank Algorithm to Rank Web Pages Inspired by Ant Colony Algorithm

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