TY - CHAP
T1 - T-Rank
T2 - Time-Aware Authority Ranking
AU - Berberich, Klaus
AU - Vazirgiannis, Michalis
AU - Weikum, Gerhard
PY - 2004/1/1
Y1 - 2004/1/1
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-540-30216-2_11
DO - 10.1007/978-3-540-30216-2_11
M3 - Chapter
AN - SCOPUS:35048841156
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 131
EP - 142
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Leonardi, Stefano
PB - Springer Verlag
ER -