Abstract
Ranking is perhaps the most important feature of a search engine, as it allows the user to efficiently order the huge amount of pages matching a query according to their relevance to the user’s information need. With respect to traditional textual search engines, Web information retrieval systems build ranking by combining at least two evidences of relevance: the degree of matching of a page—the content score—and the degree of importance of a page—the popularity score. While the content score can be calculated using one of the information retrieval models described in Chap. 3, the popularity score can be calculated from an analysis of the indexed pages’ hyperlink structure using one or more link analysis models. In this chapter we introduce the two most famous link analysis models, PageRank and HITS.
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Notes
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The diameter of the graph is logarithmically proportional to the number of its nodes.
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More precisely, a power law distribution with a≈2.1.
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Ceri, S., Bozzon, A., Brambilla, M., Della Valle, E., Fraternali, P., Quarteroni, S. (2013). Link Analysis. In: Web Information Retrieval. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39314-3_7
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