Hits algorithm

Hits algorithm

Hits algorithm is a search algorithm that is also known as hubs and authorities. It is used to distill broad search topics by identifying authorities and hubs that are joined in the link structure. The algorithm calculates two values, Hub Scores and Authority Scores, on the returned matching page after the user enters the keywords. These two values are interdependent and affect each other. The hub score measures the quality of outgoing links from a page, while the authority score measures the quality of incoming links to a page. The differences between the hub and authority scores in the HITS algorithm are that the hub score measures the quality of outgoing links, while the authority score measures the quality of incoming links.From: Intelligent Systems [2018], A real-world service mashup platform based on data integration, information synthesis, and knowledge fusion [2021], Practical Graph Mining with R [2019]

Data Mining

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Published in Bogdan M. Wilamowski, J. David Irwin, Intelligent Systems, 2018

Milos Manic

The HITS algorithm is also known as hubs and authorities and represents the distillation of broad search topics via authorities and hubs joined in the link structure. User queries present various obstacles. For example, specific queries are often associated with scarcity problem—answers are hard to find, while broad topic queries are often burdened by an abundance problem, resulting in too many hits for humans to digest. And, a “filter” idea based on the notion of authoritative pages. However, one may quickly realize that purely endogenous measures can be hard to establish. Kleinberg mentions several examples such as the term “Harvard” is not necessarily a word often used at www.harvard.edu; the term “search engines” may not be necessarily used on many of the natural authorities (Yahoo, AltaVista); or Honda or Toyota may not be using terms “auto manufacturer” on their pages [Kleinberg 98].

A real-world service mashup platform based on data integration, information synthesis, and knowledge fusion

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Published in Connection Science, 2021

Lei Yu, Yucong Duan, Kuan-Ching Li

Information theory and the HITS (Hyperlink-induced Topic Search) algorithm are used to calculate the service dependent degree. According to the HITS algorithm, after the user enters the keywords, the algorithm calculates two values on the returned matching page: Hub Scores, the other is Authority Scores, the two values are interdependent and affect each other. A hub value is the sum of the authoritative values that all the exported links on the page point to. The authority value is the sum of the hubs on the page where all the import links are located.

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A real-world service mashup platform based on data integration, information synthesis, and knowledge fusion