Author: Athena Vakali
Publication Overview
Publication period start: 2011
Number of co-authors: 13
Co-Authors
Number of publications with favourite co-authors
Productive Colleagues
Most productive colleagues in number of publications
Publications
Koutsonikola,
Vassiliki,
Vakali,
Athena
(2011):
A Clustering-Driven LDAP Framework.
In
ACM Transactions on the Web,
5
(3)
pp. 12.
https://dx.doi.org/10.1145/1993053.1993054
Pallis,
George,
Vakali,
Athena
(2006):
Insight and perspectives for content delivery networks.
In
Communications of the ACM,
49
(1)
pp. 101-106.
https://dl.acm.org/doi/10.1145/1107458.1107462
Vakali,
Athena,
Catania,
Barbara,
Maddalena,
Anna
(2005):
XML Data Stores: Emerging Practices.
In
IEEE Internet Computing,
9
(2)
pp. 62-69.
https://doi.ieeecomputersociety.org/10.1109/MIC.2005.48
Catania,
Barbara,
Maddalena,
Anna,
Vakali,
Athena
(2005):
XML Document Indexes: A Classification.
In
IEEE Internet Computing,
9
(5)
pp. 64-71.
https://doi.ieeecomputersociety.org/10.1109/MIC.2005.115
Koutsonikola,
Vassiliki A.,
Vakali,
Athena
(2004):
LDAP: Framework, Practices, and Trends.
In
IEEE Internet Computing,
8
(5)
pp. 66-72.
https://doi.ieeecomputersociety.org/10.1109/MIC.2004.44
Vakali,
Athena,
Pallis,
George
(2003):
Content Delivery Networks: Status and Trends.
In
IEEE Internet Computing,
7
(6)
pp. 68-74.
https://csdl.computer.org/comp/mags/ic/2003/06/w6068abs.htm
Zeng,
Xingjie,
Li,
Fang,
Zhang,
Dongmo,
Vakali,
Athena
(2004):
An XML-Based Bootstrapping Method for Pattern Acquisition.
In:
ICEIS 2004
,
2004,
.
pp. 303-308.
Paparrizos,
Ioannis,
Koutsonikola,
Vassiliki,
Angelis,
Lefteris,
Vakali,
Athena
(2010):
Automatic extraction of structure, content and usage data statistics of web sites.
In:
Proceedings of the 21st ACM Conference on Hypertext and Hypermedia
,
2010,
.
pp. 301-302.
https://doi.acm.org/10.1145/1810617.1810685
Karagiannidis,
Savvas,
Antaris,
Stefanos,
Zigkolis,
Christos,
Vakali,
Athena
(2010):
Hydra: an open framework for virtual-fusion of recommendation filters.
In:
Proceedings of the 2010 ACM Conference on Recommender Systems
,
2010,
.
pp. 229-232.
https://dx.doi.org/10.1145/1864708.1864754