blindly classifying new trends in incoming data

Question

How do news outlets like google news automatically classify and rank documents about emerging topics, like "Obama's 2011 budget"?

I've got a pile of articles tagged with baseball data like player names and relevance to the article (thanks, OpenCalais), and would love to create a google news-style interface that ranks and displays new posts as they come in, especially emerging topics. I suppose that a naive Bayes classifier could be trained w/ some static categories, but this doesn't allow for tracking trends like "this player was just traded to this team, these other players were also involved."

Answer 1

Texture classification is practiced in various pattern recognition applications that possess feature-liked appearance. This article tries to gather the current trends in the usage of feature extraction and classification methods used in the research of texture classification as well as the texture datasets used for the experiments. Many different feature extraction methods were introduced and used for texture classification problems. For more information regarding the same, refer to the following link: https://pdfs.semanticscholar.org/a5f1/00bb9f134b574a86a28911c54a8fc4ea7cea.pdf

The main algorithms behind Google News have been published in the academic literature by Google researchers:

• Original paper.

• Talk: Google News Personalization: Scalable Online Collaborative Filtering

• Blog discussion.

If you wish to learn more about Texture Classification then visit this Artificial Intelligence Course.