When an event occurs in the real world, numerous news reports describing this event start to appear on different news sites within a few minutes of the event occurrence. This may result in a huge amount of information for users, and automated processes may be required to help manage this information. In this paper, we describe a clustering system that can cluster news reports from disparate sources into event-centric clusters-i.e., clusters of news reports describing the same event. A user can identify any RSS feed as a source of news he/she would like to receive and our clustering system can cluster reports received from the separate RSS feeds as they arrive without knowing the number of clusters in advance. Our clustering system was designed to function well in an online incremental environment. In evaluating our system, we found that our system is very good in performing fine-grained clustering, but performs rather poorly when performing coarser-grained clustering.
We present HyperContext, a framework for adaptive and adaptable hypertext. Our fundamental premise is that when people encounter the same document, each may interpret the information it contains differently. Usually, the interpretations are not available to future users of the same information. HyperContext permits users to make these interpretations explicit, and provides support to structure hyperspace around interpretations of documents, rather than around the documents themselves. When a user browses through hyperspace, a document's context is used to determine which interpretation to present to the user. We also derive a user model of the user's short-term interests, by first representing the user's interest in the current document as a salient interpretation before combining it with the salient interpretations of other documents accessed by the user on the same path of traversal. This paper describes the adaptive features of the HyperContext framework, and presents the results of an initial evaluation of one of the features.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.