Scalable and Efficient Probabilistic Topic Model Inference for Textual Data.
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| Superior document: | Linköping Studies in Arts and Sciences Series ; v.743 |
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| Place / Publishing House: | Linköping : : Linkopings Universitet,, 2018. {copy}2018. |
| Year of Publication: | 2018 |
| Edition: | 1st ed. |
| Language: | English |
| Series: | Linköping Studies in Arts and Sciences Series
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| Online Access: | |
| Physical Description: | 1 online resource (73 pages) |
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Table of Contents:
- Intro
- ABSTRACT
- Acknowledgments
- Contents
- List of Figures
- List of Tables
- Introduction
- Background
- Motivation
- Research questions
- Thesis outline
- Bayesian inference
- Bayesian epistemology and confirmation theory
- Bayesian statistical inference
- Examples of probabilistic models
- Simulation-based statistical inference
- Probabilistic latent semantic modeling of text
- Modeling semantics
- Probabilistic modeling of textual data
- Latent semantic modeling
- Probabilistic topic models
- Practical curation of corpora and the implications for inference
- Research Questions and Summary of Contributions
- Research questions
- Summary of Contributions
- Extensions and future research
- Bibliography.