Algorithme HITS

Hyperlink-Induced Topic Search (HITS; also known as hubs and authorities) is a link analysis algorithm that rates Web pages, developed by Jon Kleinberg. The idea behind Hubs and Authorities stemmed from a particular insight into the creation of web pages when the Internet was originally forming; that is, certain web pages, known as hubs, served as large directories that were not actually authoritative in the information that they held, but were used as compilations of a broad catalog of information that led users direct to other authoritative pages. In other words, a good hub represents a page that pointed to many other pages, while a good authority represents a page that is linked by many different hubs. The scheme therefore assigns two scores for each page: its authority, which estimates the value of the content of the page, and its hub value, which estimates the value of its links to other pages. Many methods have been used to rank the importance of scientific journals. One such method is Garfield's impact factor. Journals such as Science and Nature are filled with numerous citations, making these magazines have very high impact factors. Thus, when comparing two more obscure journals which have received roughly the same number of citations but one of these journals has received many citations from Science and Nature, this journal needs be ranked higher. In other words, it is better to receive citations from an important journal than from an unimportant one. This phenomenon also occurs in the Internet. Counting the number of links to a page can give us a general estimate of its prominence on the Web, but a page with very few incoming links may also be prominent, if two of these links come from the home pages of sites like Yahoo!, Google, or MSN. Because these sites are of very high importance but are also search engines, a page can be ranked much higher than its actual relevance. In the HITS algorithm, the first step is to retrieve the most relevant pages to the search query.