Markov random topic fields
Hal Daumé · 2009
Most approaches to topic modeling assume an independence between documents that is frequently violated.We present an topic model that makes use of one or more user-specified graphs describing relationships between documents.These graph are encoded in the form of a Markov random field over topics and serve to encourage related documents to have similar topic structures.Experiments on show upwards of a 10% improvement in modeling performance.