RSSOwl Tutorial

How to get articles that reflect your interests

Impressed by an article you've read? Maybe not so much? RSSOwl lets you share your opinion of any article using the AmphetaRate "recommendation system," and, in turn, benefit from your participation in the system by automatically obtaining articles that reflect your preferences.

AmphetaRate works this way: When you rate an article, your preferences are submitted to the AmphetaRate server. When the system has collected enough rating information from you, it assigns (or reassigns) you to a collection of other users who share similar preferences (called "neighbors"). Articles from your "neighborhood" are then issued to you whenever you update your AmphetaRate feed. AmphetaRate is also using a content based Bayesian filter algorithm to calculate recommendations.

Note: Your AmphetaRate preferences data is tied to your username (described below) only, and the server does not collect any personal or machine information. Thus, if you change or reset the AmphetaRate username used in RSSOwl, you will have to retrain the ratings system as described later in this topic.

RSSOwl is installed with an AmphetaRate category and "Latest Best News" feed of articles that have been given top marks by other AmphetaRate users. You can use this newsfeed immediately, but to contribute to and gain full benefit from the rating system, you must first obtain (or enter) an AmphetaRate username and password, then "train" the system to provide the types of articles that reflect your interests.

To get or set an AmphetaRate account:

Select Preferences from the Tools menu. The Preferences dialog opens.
If it's not already selected, select the AmphetaRate item from the left pane of the dialog. If you are already registered with AmphetaRate, enter your username and password in the edit field. If you are not yet registered, enter your desired username and password and click Create Account.
Click the Apply button, then close the dialog with OK. When the dialog closes, you'll see a new feed, "Recommended Articles," in your AmphetaRate folder.

To rate an article:

Load a newsfeed from your RSS favorites (any article outside of the AmphetaRate collection), select an article in the Newsheader pane and look at its description in the News pane.
If you think you have enough information from the description to rate the article, click the Rating button/dropdown list on the News pane bar and choose a rating from "Fantastic" to "Very Bad". You can also rate the currently selected article by choosing Rate News from the Newsheader menu. Either way, your rating is immediately displayed in a small icon inside the status bar.

If you want to read the full article before deciding on a rating, click the article link in the upper portion of the News pane (or double-click the article in the Newsheader article list). The article loads into the browser. When you've read enough to decide on a rating, return to the Newsheader article list by choosing the appropriate newsfeed tab at the top of the Newsheader pane. The article you reviewed should still be selected in the article list. Rate the article by clicking the Ratings button/dropdown list in the News pane or selecting Rate News from the Newsheader menu.
Note that after rating a small icon on the right side of the status-line will turn blue. Hovering with the mouse over it will show the rating that the selected news received as tooltip.

To train the recommendation system:

If you've rated just a few articles, AmphetaRate may not yet have enough information to assign you to a "neighborhood." To help the system tailor its recommendation feed to your interests, you'll need to "train" it. As with all such processes, AmphetaRate training can take some time. Be patient with it, though--it's worth it. Here's how to get started with the training process.

Expand the AmphetaRate category in your RSS Favorites tree.
Double-click Recommended Articles. An article list appears in the Newsheader pane. If the system doesn't yet have enough data to evaluate your interests, the first item in the list reads, "Sorry, no recommendations available." Click that article and read its description in the News pane for an explanation of the training process. Then go ahead and train the system by selecting each of the training articles in the list and rating them using the steps above.
In Favorites, right-click AmphetaRate\Recommended Articles and choose Reload News from the popup menu to refresh the article set. The refreshed set may contain several grayed-out items, indicating articles you have already opened (though not necessarily rated). Whenever it's convenient for you, try reloading, rating, and refreshing to add data to your recommendation profile. At some point, you will, on a refresh, begin receiving articles tailored to your tastes and interests.