Algoritmos para avaliação de confiança em apontadores encontrados na Web

Abstract

Search engines have become an essential tool for web users today. They use algorithms to analyze the linkage relationships of the pages in order to estimate popularity for each page, taking each link as a vote of quality for pages. This information is used in the search engine ranking algorithms. However, a large amount of links found on the Web can not be considered as a good vote for quality, presenting information that can be considered as noise for search engine ranking algorithms. This work aims to detect noises in the structure of links that exist in search engine collections. We studied the impact of the methods developed here for detection of noisy links, considering scenarios in which the reputation of pages is calculated using Pagerank and Indegree algorithms. The results of the experiments showed improvement up to 68.33% in metric Mean Reciprocal Rank (MRR) for navigational queries and up to 35.36% for randomly selected navigational queries.