Object identification with attribute-mediated dependences

Authors: 
Singla, P; Domingos, P
Author: 
Singla, P
Domingos, P
Year: 
2005
Venue: 
Proceedings of PKDD-2005
URL: 
http://www.cs.washington.edu/homes/parag/papers/object-mediated-pkdd05.pdf
Citations: 
56
Citations range: 
50 - 99
AttachmentSize
Singla2005Objectidentificationwith.pdf166.6 KB

Object identifcation is the problem of determining whether
different observations correspond to the same object. It occurs in a wide
variety of fields, including vision, natural language, citation matching,
and information integration. Traditionally, the problem is solved separately
for each pair of observations, followed by transitive closure. We
propose solving it collectively, performing simultaneous inference for all
candidate match pairs, and allowing information to propagate from one
candidate match to another via the attributes they have in common. Our
formulation is based on conditional random fields, and allows an optimal
solution to be found in polynomial time using a graph cut algorithm. Parameters
are learned using a voted perceptron algorithm. Experiments
on real and synthetic datasets show that this approach outperforms the
standard one.