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T-Rank: Time-aware Authority Ranking

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44119

Berberich,  Klaus
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45660

Vazirgiannis,  Michalis
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44913

Leonardi,  Stefano
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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Zitation

Berberich, K., Vazirgiannis, M., & Weikum, G. (2004). T-Rank: Time-aware Authority Ranking. In Algorithms and Models for the Web-graph: Third International Workshop, WAW 2004 (pp. 131-142). Berlin, Germany: Springer.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2B6B-A
Zusammenfassung
Analyzing the link structure of the web for deriving a page's authority and implied importance has deeply affected the way information providers create and link content, the ranking in web search engines, and the users' access behavior. Due to the enormous dynamics of the web, with millions of pages created, updated, deleted, and linked to every day, timeliness of web pages and links is a crucial factor for their evaluation. Users are interested in important pages (i.e., pages with high authority score) but are equally interested in the recency of information. Time – and thus the freshness of web content and link structure - emanates as a factor that should be taken into account in link analysis when computing the importance of a page. So far only minor effort has been spent on the integration of temporal aspects into link analysis techniques. In this paper we introduce T-Rank, a link analysis approach that takes into account the temporal aspects freshness (i.e., timestamps of most recent updates) and activity (i.e., update rates) of pages and links. Preliminary experimental results show that T-Rank can improve the quality of ranking web pages.