Learning to extract symbolic knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create...
Publications
3 shownA comparison of event models for naive bayes text classification
Recent work in text classification has used two different first-order probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multi-va...
Using Maximum Entropy for Text Classification
This paper proposes the use of maximum entropy techniques for text classification. Maximum entropy is a probability distribution estimation technique widely used for a variety o...
Frequent Co-Authors
Researcher Info
- h-index
- 3
- Publications
- 3
- Citations
- 4,655
- Institution
- Carnegie Mellon University
External Links
Impact Metrics
h-index
3
h-index: Number of publications with at least h citations each.