9,949 research outputs found
PageRank: Standing on the shoulders of giants
PageRank is a Web page ranking technique that has been a fundamental
ingredient in the development and success of the Google search engine. The
method is still one of the many signals that Google uses to determine which
pages are most important. The main idea behind PageRank is to determine the
importance of a Web page in terms of the importance assigned to the pages
hyperlinking to it. In fact, this thesis is not new, and has been previously
successfully exploited in different contexts. We review the PageRank method and
link it to some renowned previous techniques that we have found in the fields
of Web information retrieval, bibliometrics, sociometry, and econometrics
FolkRank: A Ranking Algorithm for Folksonomies
In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006
Role of Ranking Algorithms for Information Retrieval
As the use of web is increasing more day by day, the web users get easily
lost in the web's rich hyper structure. The main aim of the owner of the
website is to give the relevant information according their needs to the users.
We explained the Web mining is used to categorize users and pages by analyzing
user's behavior, the content of pages and then describe Web Structure mining.
This paper includes different Page Ranking algorithms and compares those
algorithms used for Information Retrieval. Different Page Rank based algorithms
like Page Rank (PR), WPR (Weighted Page Rank), HITS (Hyperlink Induced Topic
Selection), Distance Rank and EigenRumor algorithms are discussed and compared.
Simulation Interface has been designed for PageRank algorithm and Weighted
PageRank algorithm but PageRank is the only ranking algorithm on which Google
search engine works.Comment: Keywords: Page Rank, Web Mining, Web Structured Mining, Web Content
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The Open Research Web: A Preview of the Optimal and the Inevitable
The multiple online research impact metrics we are developing will allow the rich new database , the Research Web, to be navigated, analyzed, mined and evaluated in powerful new ways that were not even conceivable in the paper era – nor even in the online era, until the database and the tools became openly accessible for online use by all: by researchers, research institutions, research funders, teachers, students, and even by the general public that funds the research and for whose benefit it is being conducted: Which research is being used most? By whom? Which research is growing most quickly? In what direction? under whose influence? Which research is showing immediate short-term usefulness, which shows delayed, longer term usefulness, and which has sustained long-lasting impact? Which research and researchers are the most authoritative? Whose research is most using this authoritative research, and whose research is the authoritative research using? Which are the best pointers (“hubs”) to the authoritative research? Is there any way to predict what research will have later citation impact (based on its earlier download impact), so junior researchers can be given resources before their work has had a chance to make itself felt through citations? Can research trends and directions be predicted from the online database? Can text content be used to find and compare related research, for influence, overlap, direction? Can a layman, unfamiliar with the specialized content of a field, be guided to the most relevant and important work? These are just a sample of the new online-age questions that the Open Research Web will begin to answer
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