| Download | - View accepted manuscript: A probabilistic model for fast and confident categorisation of textual documents (PDF, 325 KiB)
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| Author | Search for: Goutte, Cyril1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
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| Format | Text, Book Chapter |
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| Abstract | We describe the National Research Council's (NRC) entry in the Anomaly Detection/Text Mining competition organized at the Text Mining Workshop 2007. This entry relies on a straightforward implementation of a probabilistic categorizer described earlier [GGPC02]. This categorizer is adapted to handle multiple labeling and a piecewise-linear confidence estimation layer is added to provide an estimate of the labeling confidence. This technique achieves a score of 1.689 on the test data. This model has potentially useful features and extensions such as the use of a category-specific decision layer or the extraction of descriptive category keywords from the probabilistic profile. |
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| Publication date | 2008 |
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| Publisher | Springer |
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| Place | Oxford |
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| In | |
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| Language | English |
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| NRC number | NRCC 49829 |
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| NPARC number | 5764844 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 05e3038a-f734-4b14-bcc4-d90f41df31e8 |
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| Record created | 2009-03-29 |
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| Record modified | 2024-02-05 |
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