Vicariously Sharing Captured Web Experiences through an Automated Recommendation System
Truong, Khai Nhut
Abowd, Gregory D.
Pimentel, Maria da Graca Campos
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Our daily experiences are rich in content that we want to recall in the future. These previous experiences are often where we begin in our search for information needed when we work. In a community, we can rely on others to suggest materials when our own expertise fails to provide us with what we need. Likewise, others will make referrals only from things that they have previously experienced. In this paper, we present WebMemex, a system that recommends related Web pages to what the user is currently viewing. This system acts as an instantiation of an architecture to automatically capture and access information in a manner similar to when a person is searching for information related to her current work context where the related information being retrieved is something she has previously seen or that her friends have seen before and could ultimately suggest to her.