Existing Internet search engines use web crawlers to download data from the Web. Page quality is measured on central servers, where user queries are also processed. This paper argues that using crawlers has a list of disadvantages. Most importantly, crawlers do not scale. Even Google, the leading search engine, indexes less than 1% of the entire Web. This paper proposes a distributed search eng...

Optimizing and focusing search and results ranking in P2P networks becomes more and more important with the increasing size of these networks. Even though a few approaches have already started to investigate the computation of PageRank-like values in P2P environments, none so far has investigated how personalization could be added to it. This paper tackles the problem of distributedly computing...

As the web is escalating day by day, so people rely on the search engines to investigate the web. In this situation, the challenge for website owner is to provide relevant information to the users as per their needs and fulfill their requirements. The famous search engine Google used Hyperlink structure for ranking the web pages. There are various ranking algorithms are present for getting the ...

Traditional link analysis approaches assume equal weights assigned to different links and pages. In original PageRank formulation, the user model assumes that the user has equal probability to follow each link from a given page, thus the score of a page equally affects all of the pages it points to. It also assumes that the probability for a user to go to a URL directly without following a link...

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the ...

In recent years, information retrieval methods focusing on the link analysis have been developed; The PageRank and HITS are two typical ones According to the hierarchical organization of Web pages, we could partition the Web graph into blocks at different level, such as page level, directory level, host level and domain level. On the basis of block, we could analyze the different hyperlinks amo...

We present a very efficient semi-supervised graph-based algorithm for classification of high-dimensional data that is motivated by the MBO method of Garcia-Cardona (2014) and derived using the similarity graph. Our procedure is an elegant combination of heat kernel pagerank and the MBO method applied to study semi-supervised problems. The timing of our algorithm is highly dependent on how quick...

The Football World Cup as world’s favorite sporting event is a source of both entertainment and overwhelming amount of data about the games played. In this paper we analyse the available data on football world championships since 1930 until today. Our goal is to rank the national teams based on all matches during the championships. For this purpose, we apply the PageRank with restarts algorithm...

Keyword and keyphrase extraction is an important problem in natural language processing, with applications ranging from summarization to semantic search to document clustering. Graph-based approaches to keyword and keyphrase extraction avoid the problem of acquiring a large in-domain training corpus by applying variants of PageRank algorithm on a network of words. Although graph-based approache...