Ernest P. Chan

Learn More
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously used with supervised training data for a fixed query. When only noisy, unsupervised training data generated from a heuristic relevance-scoring formula are available, two crucial(More)
  • Mohd Othman, Fairuz Iskandar, Ernest Chan, Karen J Nelson, Timbrell, Gregory T +4 others
  • 2011
(2011) Barriers to information technology gover-nance adoption : a preliminary empirical investigation. Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source: Abstract The adoption of IT Governance(More)
  • 1