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Gianni Morini

dblp:12/3705 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
ranking
0.012003
Adaptive ranking of web pages · WWW 2003
Information retrieval › ranking › search ranking
web ranking
0.012003
Adaptive ranking of web pages · WWW 2003
Mathematical optimization › continuous optimization › nonlinear optimization
quadratic programming
0.012003
Adaptive ranking of web pages · WWW 2003

Methods — techniques the papers use, named apart from their topics

quadratic programming · 0.1clustering · 0.1
YearPublicationVenuePosition
2003 Adaptive ranking of web pages
abstract
In this paper, we consider the possibility of altering the PageRank of web pages, from an administrator's point of view, through the modification of the PageRank equation. It is shown that this problem can be solved using the traditional quadratic programming techniques. In addition, it is shown that the number of parameters can be reduced by clustering web pages together through simple clustering techniques. This problem can be formulated and solved using quadratic programming techniques. It is demonstrated experimentally on a relatively large web data set, viz., the WT10G, that it is possible to modify the PageRanks of the web pages through the proposed method using a set of linear constraints. It is also shown that the PageRank of other pages may be affected; and that the quality of the result depends on the clustering technique used. It is shown that our results compared well with those obtained by a HITS based method.
Ah Chung Tsoi, Gianni Morini, Franco Scarselli, Markus Hagenbuchner, Marco Maggini
WWW2