We have recruited around 20 volunteers (researchers, academics and PhD students) to test the following use case for the Bayesian Feed Filtering project.
* Research staff who want to monitor research findings and opportunities from a wide range of sources but who are only interested in a specific research field.
The first stage of the trial involves a short questionnaire about the researchers methods of current awareness of journal articles and the expectations required of such a filtering service. The users have submitted a list of Journals that have RSS Feeds (from ticTOCs) to be added to the database. We are using a customised version Sux0r which will be performing the Bayesian Filtering. For the trial we have created accounts for each user, submitted RSS feeds for the journals they follow and set up a vector and categories against which articles can be placed. For this particular use case we created a Vector called “Interestingness” with two categories “Interesting” or “Not Interesting”. The volunteers were demonstrated how to train articles from the RSS feeds into the two categories and also how to “top-up” the train by submitting other interesting articles which are not available as RSS.
I hope to have conducted all the initial interviews with the volunteers by the 4th of September, allowing users 3-4 weeks of training. A second interview will be conducted at the end of October, to determine whether the Bayesian Filter is successful in correctly categorising new articles collected that month.