Page-reRank Using Trusted Links to Re-Rank Authority

• Published in: IEEE/WIC/ACM International Conference on web intelligence pp. 614 - 617
• Main Authors: Massa, Paolo, Hayes, Conor
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 19.09.2005; IEEE
• Series: ACM Conferences
• Subjects: Applied computing > Document management and text processing > Document preparation > Multi > mixed media creation; Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Semantic networks; Content based retrieval; Filtering; HTML; Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Hypertext > hypermedia; Humans; Information resources; Information systems > Information retrieval; Information systems > Information storage systems; Intelligent networks; Joining processes; Search engines; Uniform resource locators; Web pages
• ISBN: 076952415X; 9780769524153
• DOI: 10.1109/WI.2005.112

Search engines like Google.com use the the link structure of the Web to determine whether web pages are authoritative sources of information. However, the linking mechanism provided by HTML does not allow the web author to express different types of links, such as positive or negative endorsements of page content. As a consequence, search engine algorithms cannot discriminate between sites that are highly linked and sites that are highly trusted. We demonstrate our claim by running PageRank on a real world data set containing positive and negative links. We conclude that simple semantic extensions to the link mechanism would provide a richer semantic network from which to mine more precise Web Intelligence.