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We report on our ongoing study of using the genre of Web pages to facilitate information exploration. By genre, we mean socially recognized regularities of form and purpose in documents (e.g., a letter, a memo, a research paper). Our study had three phases. First, through a user study, we identified genres which most/least frequently meet searchers'(More)
Cluster retrieval assumes that the probability of relevance of a document should depend on the relevance of other similar documents to the same query. The goal is to find the best group of documents. Many studies have examined the effectiveness of this approach, by employing different retrieval methods or clustering algorithms, but few have investigated(More)
The most common approach to cluster-based retrieval is to retrieve one or more clusters in their entirety to a query. The system's goal is to assign top ranks to the clusters that give best retrieval performance, out of all clusters. Previous research in this area has suggested that " optimal " clusters exist that, if retrieved, would yield very large(More)
This paper describes a question answering system that automatically finds answers to questions in a large collection of documents. The prototype CNLP question answering system was developed for participation in the TREC-9 question answering track. The system uses a two-stage retrieval approach to answer finding based on keyword and named entity matching.(More)