Data Clustering via Dimension Reduction and Algorithm Aggregation
| dc.contributor.advisor | Ernest Stitzinger, Committee Member | en_US |
| dc.contributor.advisor | Carl Meyer, Committee Chair | en_US |
| dc.contributor.advisor | Ilse Ipsen, Committee Member | en_US |
| dc.contributor.author | Race, Shaina L | en_US |
| dc.date.accessioned | 2010-04-02T18:09:43Z | |
| dc.date.available | 2010-04-02T18:09:43Z | |
| dc.date.issued | 2008-11-07 | en_US |
| dc.degree.discipline | Applied Mathematics | en_US |
| dc.degree.level | thesis | en_US |
| dc.degree.name | MS | en_US |
| dc.description.abstract | We focus on the problem of clustering large textual data sets. We present 3 well-known clustering algorithms and suggest enhancements involving dimension reduction. We propose a novel method of algorithm aggregation that allows us to use many clustering algorithms at once to arrive on a single solution. This method helps stave off the inconsistency inherent in most clustering algorithms as they are applied to various data sets. We implement our algorithms on several large benchmark data sets. | en_US |
| dc.identifier.other | etd-08182008-172335 | en_US |
| dc.identifier.uri | http://www.lib.ncsu.edu/resolver/1840.16/2029 | |
| dc.rights | I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dis sertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. | en_US |
| dc.subject | dimension reduction | en_US |
| dc.subject | nonnegative matrix factorization | en_US |
| dc.subject | document clustering | en_US |
| dc.subject | data clustering | en_US |
| dc.subject | singular value decomposition | en_US |
| dc.subject | clustering algorithms | en_US |
| dc.title | Data Clustering via Dimension Reduction and Algorithm Aggregation | en_US |
Files
Original bundle
1 - 1 of 1
