Posts with keyword: machine+learning

2 entries

Finding Quality Blogs

Thu May 10 14:22:00 2007

This talk entitled "Exploring in the Weblog Space by Detecting Informative and Affective Articles" by researchers from Shanghai Jiao-Tong University (see full paper) describes the use of machine learning techniques to classify blogs and blog articles according to the amount of "informative" and "affective" information in the blog. Affective here is a fancy word for "touchy-feely." The authors use various discrimination techniques and give results on which are the best for their purposes. The propose that being able to find blogs and blog articles they classify as "informative" leads to information, usually by experts, and is the kind of
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Bayesian Networks in Ruby

Fri Mar 16 13:13:00 2007

Carl Youngblood is speaking on Bayesian networks in Ruby. He starts by pointing out that building complete logical systems by building rules is necessarily a futile task. The answer? A system that accounts for ignorance and degree of belief probabilistically. He quote Norvig: "Probability provides a way of summarizing the uncertainty that comes from our laziness and ignorance." After a brief tutorial on how probability can be used to overcome the weaknesses of predicate logic, Carl launches a discussion of Bayesian inference and networks. That took quite a while, but was a good tutorial on the problems. Carl is
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