Abstract
A key task in an extraction system for query-oriented multi-document summarisation, necessary for computing relevance and redundancy, is modelling text semantics. In the Embra system, we use a representation derived from the singular value decomposition of a term co-occurrence matrix. We present methods to show the reliability of performance improvements. We find that Embra performs better with dimensionality reduction.
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CITATION STYLE
Hachey, B., Murray, G., & Reitter, D. (2006). Dimensionality Reduction Aids Term Co-Occurrence Based Multi-Document Summarization. In COLING ACL 2006 - Task-Focused Summarization and Question Answering, Proceedings of the Workshop (pp. 1–7). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1654679.1654681
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