Recent studies show that the link-structure-based measures of Web page popularity prolong the procedure of new pages reaching their deserved ranking. In this paper we propose a promotional ranking scheme that offers an opportunity for newly-created pages to be recognized.We conduct a simulation to evaluate our method. Experimental results show that our method remarkably raises the probability f...

Current search engines generally employ link analysis techniques to web-page re-ranking. However, the same techniques are problematic in small webs, such as websites or intranet webs, because the link structure is different from the global Web. We propose a re-ranking mechanism based on implicit links generated from user access patterns. Experimental results indicate that our method outperforms...

Design: The authors measured Wikipedia’s ranking on general Internet search engines by entering keywords from MedlinePlus, NHS Direct Online, and the National Organization of Rare Diseases as queries into search engine optimization software. We assessed whether article quality influenced this ranking. The authors tested whether traffic to Wikipedia coincided with epidemiological trends and news...

We introduce a new approach for ranking Web pages to capture the extent to which the whole Web depends on an individual Web page. The importance of a Web page is measured by how much the Web changes when the page is disconnected from the Web. While there are potentially many useful ways to quantify the change, in this work we focus on the following: represent the state of the Web by the output ...

Background. Although the World Taekwondo federation currently applies the APIS ranking method to calculate the Olympic rankings, some limitations exist. Objectives. This study applies the PageRank model to Olympics Taekwondo rankings. Methods. The 2015-2018 World Taekwondo Grand Prix competition results for women’s four weight classes (-49kg, -57kg, -67kg, +67kg) were used as research data, t...

Algorithms for ranking of web pages such as Google PageRank assign importance scores according to a stationary distribution of a Markov random walk on the web graph. Although in the classical search scheme the ranking scores are pre-computed off-line, several challenging problems in contemporary web search, such as personalized search and search in entity graphs, require on-line PageRank comput...

A large amount of new information is posted on the Web every day. Large-scale web search engines often update their index slowly and are unable to present such information in a timely manner. In this thesis, we present our solutions of searching new information from the web by tracking the changes of web documents. First, we present the algorithms and techniques useful for solving the following...

In this paper, the authors attempt to compute a global ranking for all web pages, based solely on their location in the Web’s graph structure. This PageRank indicates the importance of each page. Once again, the Web is modeled as a directed graph G = (V;E), where V is the set of nodes (pages) and E the set of edges and there exists an edge (i; j) from node i to node j in the graph if and only i...

Contextual advertising systems place ads automatically in Web pages, based on the Web page content. In this paper we present a machine learning approach to contextual advertising using a novel set of features which aims to capture subtle semantic associations between the vocabularies of the ad and the Web page. We design a model for ranking ads with respect to a page which is learned using Supp...