Who links to whom: mining linkage between Web sites

Bharat, Krishna; Chang, Bay-Wei; Henzinger, Monika; Ruhl, Matthias

doi:10.1109/icdm.2001.989500

Cited by 108 publications

(97 citation statements)

References 17 publications

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“…Bharat et al [2] have shown that there are two different types of web links dominating the web structure, "intra-site" links and "inter-site" ones. A "site" can be a domain (.yahoo.com), a host (geocities.yahoo.com) or a directory on a web server (http://www.geocities.com/someuser/).…”

Section: Host-based Link Localitymentioning

confidence: 99%

Efficient Parallel Computation of PageRank

Kohlschütter

Chirita

Nejdl

2006

Lecture Notes in Computer Science

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Abstract. PageRank inherently is massively parallelizable and distributable, as a result of web's strict host-based link locality. In this paper we show that the Gauß-Seidel iterative method for solving linear systems can be successfully applied in such a parallel ranking scenario in order to improve convergence. By introducing a two-dimensional web model and by adapting the PageRank to this environment, we present and evaluate efficient methods to compute the exact rank vector even for large-scale web graphs in only a few minutes and iteration steps, with intrinsic support for incremental web crawling, and without the need for page sorting/reordering or for sharing global information.

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Section: Host-based Link Localitymentioning

confidence: 99%

Efficient Parallel Computation of PageRank

Kohlschütter

Chirita

Nejdl

2006

Lecture Notes in Computer Science

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“…The first papers to raise the issue were [27,18]. The spammers' success was noted in [2,9,10,11,19].…”

Section: Introductionmentioning

confidence: 99%

“…Web spamming has received a lot of attention lately [2,3,10,11,15,17,18,20,23,26,27,30]. The first papers to raise the issue were [27,18].…”

Section: Introductionmentioning

confidence: 99%

Web Spam, Social Propaganda and the Evolution of Search Engine Rankings

Metaxas

2010

Lecture Notes in Business Information Processing

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Summary. Search Engines have greatly influenced the way we experience the web. Since the early days of the web, users have been relying on them to get informed and make decisions. When the web was relatively small, web directories were built and maintained using human experts to screen and categorize pages according to their characteristics. By the mid 1990's, however, it was apparent that the human expert model of categorizing web pages does not scale. The first search engines appeared and they have been evolving ever since, taking over the role that web directories used to play.But what need makes a search engine evolve? Beyond the financial objectives, there is a need for quality in search results. Search engines know that the quality of their ranking will determine how successful they are. Search results, however, are not simply based on well-designed scientific principles, but they are influenced by web spammers. Web spamming, the practice of introducing artificial text and links into web pages to affect the results of web searches, has been recognized as a major search engine problem. It is also a serious users problem because they are not aware of it and they tend to confuse trusting the search engine with trusting the results of a search.In this paper, we analyze the influence that web spam has on the evolution of the search engines and we identify the strong relationship of spamming methods on the web to propagandistic techniques in society. Our analysis provides a foundation for understanding why spamming works and offers new insight on how to address it. In particular, it suggests that one could use social anti-propagandistic techniques to recognize web spam.

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“…Identifying the boundary of a web-site can automate the choice of pages to archive. Studying the world-wide web at web-site level rather than web-page level may also have useful applications [3].Documents can be represented by multiple pages on the web [5]. Thus, sometimes, it is not reasonable to study attributes like authorship at page level.…”

Section: Introductionmentioning

confidence: 99%

Web-Site Boundary Detection

Alshukri

Coenen

Zito

2010

Advances in Data Mining. Applications and Theoretical Aspects

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Abstract. Defining the boundaries of a web-site, for (say) archiving or information retrieval purposes, is an important but complicated task. In this paper a web-page clustering approach to boundary detection is suggested. The principal issue is feature selection, hampered by the observation that there is no clear understanding of what a web-site is. This paper proposes a definition of a web-site, founded on the principle of user intention, directed at the boundary detection problem; and then reports on a sequence of experiments, using a number of clustering techniques, and a wide range of features and combinations of features to identify web-site boundaries. The preliminary results reported seem to indicate that, in general, a combination of features produces the most appropriate result.

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Who links to whom: mining linkage between Web sites

Abstract: Abstract

Cited by 108 publications

References 17 publications

Efficient Parallel Computation of PageRank

Efficient Parallel Computation of PageRank

Web Spam, Social Propaganda and the Evolution of Search Engine Rankings

Web-Site Boundary Detection

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