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IR Yi Zhang's term projectBasic Information
(cooperate with Jade Goldstein)
Contents
AbstractFor
most of the text summarization task, people approach the problem by generating
summaries from the document, which is usually the way human abstracters do using
a model like: Document ->
Abstract On the other hand, when writing an article, such as a research paper, people often first have some idea about what is the main idea, then write an outline, finally write the whole article according to the outline. we can view the process as a generative model like: Semantic structures -> Outline (Abstract )-> Document ( ) In my project, I will use this model to do text summarization task ProposalTimelines
System DescriptionPart1: Neural Network Part2: Maximum Entropy Model Part3: Combination of NN result and ME result Presentation and ResultsFinal reportConclusionsReferenceA maximum entropy approach to natural language processing , by Adam L. Berger OCELOT: A system for summarizing web pages by Adam L.Berger, Vibhu O. Mittal A Comparision of Ranking Rankings Produced by Summarization Evaluation Measures by Robert L. Donaway ,Kevin W. Drummey, Laura A. Mather Summarizing Text
Documents: Sentence Selection and Evaluation Metrics , by Jade
Goldstein, Mark Kantrowitz, Vibhu Mittal and Jaime Carbonell , SIGIR 99
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