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Automatic Summarization from Multiple Documents (2009)
| Content Provider | CiteSeerX |
|---|---|
| Author | Giannakopoulos, George |
| Abstract | This work reports on research conducted on the domain of multi-document summarization using background knowledge. The research focuses on summary evaluation and the implementation of a set of generic use tools for NLP tasks and especially for automatic summarization. Within this work we formalize the n-gram graph representation and its use in NLP tasks. We present the use of n-gram graphs for the tasks of summary evaluation, content selection, novelty detection and redundancy removal. Furthermore, we present a set of algorithmic constructs and methodologies, based on the notion of n-gram graphs, that aim to support meaning extraction and textual quality quantification. |
| File Format | |
| Publisher Date | 2009-01-01 |
| Access Restriction | Open |
| Subject Keyword | Textual Quality Quanti Fication Multi-document Summarization Multiple Document Redundancy Removal Generic Use Tool Novelty Detection Automatic Summarization N-gram Graph Summary Evaluation Nlp Task N-gram Graph Representation Background Knowledge Algorithmic Construct |
| Content Type | Text |
