BayesFF: Final post

Diagram of prototype: schematically we can show how the prototype supports the aggregation and of RSS feeds comprising table of contents information from selected journals and filters them (using pre-existing software called sux0r) into two feeds, one of which is has information about those papers that are predicted to be relevant to a user’s research interests. The project has added the ability to interact with sux0r through third-party software.

Our work has shown how effectively this works for a trial group of researchers; in most cases, after sufficient training of the system, the outgoing feeds were successfully filtered so that one contained a significantly higher concentration of interesting items than the raw feeds and the other did not contain a significant number of interesting items.

End User of Prototype:
We have an installation of sux0r which people are welcome to register on and which can be used to set up feeds for aggregation (you will not automatically be given sufficient privileged to approve feeds, so it is best to contact the project about this). The base URL for the API for this installation is and the API calls which have been implements are documented in the following posts on this blog: Return RSS items for a user and ReturnVectors and ReturnCategories. Also available: a summary of other features for the API have been scoped. The latest update was 08 December 2009.

Here’s a screen cast of Lisa using the API

(NB the version at the end of the link is a whole lot clearer than the embedded YouTube version, especially if you click on the view in HD option).

The code for our work on the API is in a branch of the main sux0r repository on sourceForge.

Project Team
Phil Barker,, Heriot-Watt University (project manager)
Santiago Chumbe,, Heriot-Watt University (developer)
Lisa J Rogers,, Heriot-Watt University (researcher)

Project Website:
PIMS entry:

Table of Content for Project Posts
Development work

User trialling

Community Engagement

Project Mangement



Filed under management

2 responses to “BayesFF: Final post

  1. Good stuff! And described accurately. Might be nice to have a voice-over with the screencast explaining what is going on, especially since it is hard to read the URL. Also well done on the project blog, an artefact that is well worth telling people about well beyond the life of the project. Thanks for all your hard work.

  2. Hi David,

    Thanks for the feedback, I have updated the screencast which now contains a voice-over.

    This version on Screenr is better quality than the YouTube version