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Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/1476

Authors: Provost, JAMES

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Keywords: automated summarization
singular value decomposition
tag clouds
Issue Date: 2008
Series/Report no.: Canadian theses
Abstract: Automated summarization is a difficult task. World-class summarizers can provide only "best guesses" of which sentences encapsulate the important content from within a set of documents. As automated systems continue to improve, users are still not given the means to observe complex relationships between seemingly independent concepts. In this research we used singular value decompositions to organize concepts and determine the best candidate sentences for an automated summary. The results from this straightforward attempt were comparable to world-class summarizers. We then included a clustered tag cloud, using a singular value decomposition to measure term "interestingness" with respect to the set of documents. The combination of best candidate sentences and tag clouds provided a more inclusive summary than a traditionally-developed summarizer alone.
Description: Thesis (Master, Computing) -- Queen's University, 2008-09-24 16:31:25.261
URI: http://hdl.handle.net/1974/1476
Appears in Collections:Queen's Graduate Theses and Dissertations
School of Computing Graduate Theses
Department of Economics Graduate Theses

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