Tag Archives: demonstrator

How To Use Bayesian Feed Filter

I have created 5 screen casts showing users how to use the Bayesian Feed Filter.

  1. How to Register an account on Bayesian Feed Filter http://screenr.com/WkA
    • Go to http://icbl.macs.hw.ac.uk/sux0r206/
    • Click on Register (Top Right of Screen)
    • Enter a Nickname, Email Address and Password
    • Verify Your Password
    • Add Any Additional Information
    • Enter the Anti-Spam Code
    • Click Submit
  2. How to Login and Subscribe to RSS Feeds http://screenr.com/ckA
    • Once you have registered an account click on Login (Top Right of Screen)
    • Enter your Nickname and Password
    • Click on Feeds (You will be presented with a list of all feeds on your first login)
    • Scroll to the bottom of the list and click on Manage Feeds
    • Select the Checkboxes of the feeds you would like to subscribe to
    • Click Submit
    • You can add a new feed by clicking on Suggest Feed (an administrator will need to approve the feed first)
    • You can browse the feeds by clicking on the titles of the feeds
  3. How to train Bayesian Feed Filter to Filter your RSS Feeds http://screenr.com/3kA
    • Once you have logged in to your account and subscribed to some feeds you can start training
    • Click on your nickname (Top right ofthe screen)
    • Click on Edit Bayesian
    • Enter the name of a vector (list of categories) and click add (in this case the vector is called Interestingness)
    • Enter the name of your first category and click add (in this case Interesting)
    • Enter the name of your secondcategory and click add (in this case Not Interesting)
    • Click On your nickname then on Feeds
    • You can start training items by clicking on the drop down menu of categories
    • If the item is already displaying the category you wish to train it in you will first need to select the other category then reselect the correct category
    • Items that have been trained will display the Vector as green text
  4. How to train Bayesian Feed Filter using other documnets http://screenr.com/vSK
    • Once you have logged in to your account and subscribed to some feeds you can start training
    • Click on your nickname (Top right of the screen)
    • Click on Edit Bayesian
    • Copy and paste text from other documents into the Train Document text area
    • Select the category and click train
    • You can also categorise other documents
    • Copy and paste text from other documents into the Categorize Document text area
    • Select the vector and click categorize.
    • The probability of the document belonging to each category in the vector will be displayed.
  5. How to view filtered RSS Items by threshold/keywords http://screenr.com/y1K
    • Click on Feeds
    • At the top of the screen select the category and set a threshold
    • Click on threshold
    • Only the items relevant to the selected categroy above the set threshold are displayed
    • To filter by keywords, type your keywords into the keywords text box
    • Click on threshold
    • Only the items containing those keywords will be displayed

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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 http://icbl.macs.hw.ac.uk/sux0rAPI/icbl/ 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, philb@icbl.hw.ac.uk, Heriot-Watt University (project manager)
Santiago Chumbe, S.Chumbe@hw.ac.uk, Heriot-Watt University (developer)
Lisa J Rogers, l.j.rogers@hw.ac.uk, Heriot-Watt University (researcher)

Project Website: http://www.icbl.hw.ac.uk/bayesff/
PIMS entry: https://pims.jisc.ac.uk/projects/view/1360

Table of Content for Project Posts
Development work

User trialling

Community Engagement

Project Mangement

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