Chapter: Topic Models for NLP Applications

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Home > Encyclopedia of Machine Learning and Data Science > Topic Models for NLP Applications

Encyclopedia of Machine Learning and Data Science |

Dinh Phung; Geoffrey I. Webb; Claude Sammut

Springer US

Topic Models for NLP Applications

Chapter Info

Authors

Zhiyuan Chen; Bing Liu

ARI Id

1665195388475_5259342

Access

Not Available Free

DOI

10.1007/978-1-4899-7502-7_906-1

Chapter URL

https://rd.springer.com/referenceworkentry/10.1007/978-1-4899-7502-7_906-1

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Chapters/Headings	Author(s)	Pages	Info
K-Means Clustering	Xin Jin; Jiawei Han
K-Medoids Clustering	Xin Jin; Jiawei Han
K-Way Spectral Clustering	Xin Jin; Jiawei Han
Abduction	Antonis C. Kakas
Adaptive Resonance Theory	Gail A. Carpenter; Stephen Grossberg
Adversarial Attacks on Anomaly Detection	Arjun Nitin Bhagoji; Paria Shirani
Adversarial Learning on Malware	Christopher Molloy; Ziad Mansour; Steven H. H. Ding
Anomaly Detection	Varun Chandola; Arindam Banerjee; Vipin Kumar
Anonymizing Trajectory Data	Khalil Al-Hussaeni
Authorship Analysis with Machine Learning	Waqas Ahmed; Abdul Rehman Javed; Zunera Jalil; Farkhund Iqbal
Autonomous Helicopter Flight Using Reinforcement Learning	Adam Coates; Pieter Abbeel; Andrew Y. Ng
Average-Reward Reinforcement Learning	Prasad Tadepalli
Bayes’ Rule	Geoffrey I Webb
Bias-Variance Trade-offs: Novel Applications	Dev Rajnarayan; David Wolpert
Biomedical Informatics	C. David Page; Sriraam Natarajan
Boltzmann Machines	Geoffrey Hinton
Cascade–Correlation	Thomas R. Shultz; Ardavan S. Nobandegani; Scott E. Fahlman
Case-Based Reasoning	Susan Craw
Categorical Data Clustering	Periklis Andritsos; Panayiotis Tsaparas
Causality	Ricardo Silva
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