Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Building classifiers using Bayesian networks
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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Text classification is becoming an interesting research field due to increased availability of documents in digital form which is necessary to organize. The machine learning paradigm is usually applied to text classification, according to which a general inductive process automatically builds an text classifier from a set of pre-classified documents. In this paper we investigate the application of Bayesian networks to classify MedLine documents, where each document is identified by a set of MeSH ontology terms. Bayesian networks have been selected for their ability to describe conditional independencies between variables and provide clear methodologies for learning from observations.Our experimental evaluation of these ideas is based on the relevance judgments of the 2004 TREC workshop Genomics track.