%0 Generic %1 hachey2006dimensionality %A Hachey, Ben %A Murray, Gabriel %A Reitter, David %B Proceedings of the COLING-ACL Workshop Task-Focused Summarization and Question Answering 2006 %C Sydney, Australia %D 2006 %K imported %P 1-7 %T Dimensionality Reduction Aids Term Co-Occurrence Based Multi-Document Summarization %X 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.

@conference{hachey2006dimensionality, 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.}, added-at = {2009-10-29T03:50:14.000+0100}, address = {Sydney, Australia}, author = {Hachey, Ben and Murray, Gabriel and Reitter, David}, bdsk-url-1 = {http://www.david-reitter.com/compling/papers/hachey2006dimensionality.pdf}, biburl = {https://www.bibsonomy.org/bibtex/2ce809d4fb59a863a4f91b724d60071cc/davidswelt}, booktitle = {Proceedings of the COLING-ACL Workshop Task-Focused Summarization and Question Answering 2006}, date-added = {2006-05-23 11:04:02 +0100}, date-modified = {2008-01-28 16:54:12 +0000}, interhash = {59a708a51c60eedef4918d18d14ae391}, intrahash = {ce809d4fb59a863a4f91b724d60071cc}, keywords = {imported}, pages = {1-7}, pubtype = {refereed-ws}, timestamp = {2009-10-29T03:50:14.000+0100}, title = {Dimensionality Reduction Aids Term Co-Occurrence Based Multi-Document Summarization}, year = 2006 }