automatically sharing web experiences through a hyperdocument recommender system
As an approach that applies not only to support user navigation on the Web, recommender systems have been built to assist and augment the natural social process of asking for recommendations from other people. In a typical recommender system, people provide suggestions as inputs, which the system aggregates and directs to appropriate recipients. In some cases, the primary computation is in the aggregation; in others, the value of the system lies in its ability to make good matches between the recommenders and those seeking recommendations.In this paper, we discuss the architectural and design features of WebMemex, a system that (a) provides recommended information based on the captured history of navigation from a list of people well-known to the users --- including the users themselves, (b) allows users to have access from any networked machine, (c) demands user authentication to access the repository of recommendations and (d) allows users to specify when the capture of their history should be performed.
web recommender systems information retrieval open hypermedia semantic structures