AOL have just added a nice new feature to their beta RSS aggregator called personalised content recommendations.
“We hope that our recommendations can help you to combat information overload as well as introduce you to appealing content suggestions.”
Recommendations were added in a two pane design highlighted in the lower pane of My AOL below, The two panes are explained as follows:
1.) Recommended Content (left) – These are personalised content recommendations. As you click on headlines within My AOL, AOL “learn” what you like and suggest similar stories. This information is used solely within My AOL and strictly for the purpose of delivering new, relevant content to you. Your preferences are stored in your history file, you can clear that file at any time.
2.) People Like Me Content (right)– Leverages “wisdom of the crowds” to offer additional suggested readings. As other people use My AOL, they occasionally click on stories that are similar to the items you have selected. The AOL system recognises these similarities and provides additional content that might be of interest to you. This information is stored in your history file, which you can clear at any time. Both of these features use a simple and confidential process used to provide friendly suggestions: We hope you find something you like!
This feature is based on the attention metadata stored in your history file. AOL appear to be aggregating this centrally in order to then make recommendations based on what everyone clicked on. This is a good step forward in helping people discover new feeds, although I doubt it will help fix the information overload problem in fact I think it will probably add to the overload burden.
What this new service lacks is a social discovery element so that the recommendations only come from people in your trusted network – family, friends, co-workers etc. but that might be in the next version?