Scalable Text Mining with Sparse Generative Models
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Scalable Text Mining with Sparse Generative Models
Summary
Scalable Text Mining with Sparse Generative Models is a doctoral thesis[1].
Key Facts
- Scalable Text Mining with Sparse Generative Models's instance of is recorded as doctoral thesis[2].
- Scalable Text Mining with Sparse Generative Models was published by Waikato Research Commons[3].
- Scalable Text Mining with Sparse Generative Models's place of publication is recorded as Hamilton[4].
- Scalable Text Mining with Sparse Generative Models's language of work or name is recorded as English[5].
- Scalable Text Mining with Sparse Generative Models's country of origin is recorded as New Zealand[6].
- Scalable Text Mining with Sparse Generative Models was published on 2015[7].
- Scalable Text Mining with Sparse Generative Models's main subject is information retrieval[8].
- Scalable Text Mining with Sparse Generative Models's main subject is machine learning[9].
- Scalable Text Mining with Sparse Generative Models's main subject is text classification[10].
- Scalable Text Mining with Sparse Generative Models's work available at URL is recorded as https://researchcommons.waikato.ac.nz/handle/10289/9435[11].
- Scalable Text Mining with Sparse Generative Models's title is recorded as Scalable Text Mining with Sparse Generative Models[12].
- Scalable Text Mining with Sparse Generative Models's author name string is recorded as Antti Puurula[13].
- Scalable Text Mining with Sparse Generative Models's thesis submitted to is recorded as University of Waikato[14].
- Scalable Text Mining with Sparse Generative Models's on focus list of Wikimedia project is recorded as NZThesisProject[15].
- Scalable Text Mining with Sparse Generative Models's copyright status is recorded as copyrighted[16].
- Scalable Text Mining with Sparse Generative Models's online access status is recorded as open access[17].
- Scalable Text Mining with Sparse Generative Models's thesis committee member is recorded as Ian H. Witten[18].
- Scalable Text Mining with Sparse Generative Models's thesis committee member is recorded as Lynette Ann Hunt[19].
- Scalable Text Mining with Sparse Generative Models's thesis committee member is recorded as Geoffrey Holmes[20].
- Scalable Text Mining with Sparse Generative Models's thesis submitted for degree is recorded as Doctor of Philosophy[21].
Body
Designation and Status
Scalable Text Mining with Sparse Generative Models's instance of is recorded as doctoral thesis[2].