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DALT
2008
Springer
14 years 11 months ago
Abstracting and Verifying Strategy-Proofness for Auction Mechanisms
ing and Verifying Strategy-proofness for Auction Mechanisms E. M. Tadjouddine, F. Guerin, and W. Vasconcelos Department of Computing Science, King's College, University of Abe...
Emmanuel M. Tadjouddine, Frank Guerin, Wamberto We...
CHI
2011
ACM
14 years 1 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
CIKM
2009
Springer
15 years 4 months ago
Helping editors choose better seed sets for entity set expansion
Sets of named entities are used heavily at commercial search engines such as Google, Yahoo and Bing. Acquiring sets of entities typically consists of combining semi-supervised exp...
Vishnu Vyas, Patrick Pantel, Eric Crestan
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
15 years 2 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
BMCBI
2005
251views more  BMCBI 2005»
14 years 10 months ago
Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...