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ICDAR
2009
IEEE
16 years 1 months ago
Learning Rich Hidden Markov Models in Document Analysis: Table Location
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
Ana Costa e Silva
RECSYS
2009
ACM
16 years 1 months ago
Learning to recommend helpful hotel reviews
User-generated reviews are a common and valuable source of product information, yet little attention has been paid as to how best to present them to end-users. In this paper, we d...
Michael P. O'Mahony, Barry Smyth
ACCV
2007
Springer
16 years 28 days ago
Learning a Fast Emulator of a Binary Decision Process
Abstract. Computation time is an important performance characteristic of computer vision algorithms. This paper shows how existing (slow) binary-valued decision algorithms can be a...
Jan Sochman, Jiri Matas
OZCHI
2006
ACM
16 years 21 days ago
Learning from interactive museum installations about interaction design for public settings
This paper reports on the evaluation of a digitallyaugmented exhibition on the history of modern media. We discuss visitors’ interaction with installations and corresponding int...
Eva Hornecker, Matthias Stifter
ICFCA
2005
Springer
16 years 7 days ago
Lessons Learned in Applying Formal Concept Analysis to Reverse Engineering
A key difficulty in the maintenance and evolution of complex software systems is to recognize and understand the implicit dependencies that define contracts that must be respecte...
Gabriela Arévalo, Stéphane Ducasse, ...