Here is a paper that details the back ground material, the program architecture and the methods employed in the project.


The author will demonstrate that text data from an Online Social Network can be tokenized, filtered, expanded with synonyms and rated with an approximated Vector State Model cosine Θ function.  The resulting value is used by an agent to rate and possibly filter subscribed content.  Additionally, the agent can monitor a public content source and identify and display  content that may be potentially interesting to the consumer.


There are several ideas mentioned at the end of the paper for possible future development.  If you are interested in using SkimmerAgent as a starting point for a project or in contributing to the application please contact me.