Concepts inAccounting for burstiness in topic models
Topic model
In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. An early topic model was described by Papadimitriou, Raghavan, Tamaki and Vempala in 1998. Another one, called Probabilistic latent semantic indexing (PLSI), was created by Thomas Hofmann in 1999.
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Burst transmission
In telecommunication, the term burst transmission or data burst has the following meanings: Any relatively high-bandwidth transmission over a short period. For example, a download might use 2 Mbit/s on average, while having "peaks" bursting up to, say, 2.4 Mbit/s. Transmission that combines a very high data signaling rate with very short transmission times - i.e. , the message is compressed.
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Accountancy
Accountancy is the process of communicating financial information about a business entity to users such as shareholders and managers. The communication is generally in the form of financial statements that show in money terms the economic resources under the control of management; the art lies in selecting the information that is relevant to the user and is reliable.
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Latent Dirichlet allocation
In statistics, latent Dirichlet allocation (LDA) is a generative model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. For example, if observations are words collected into documents, it posits that each document is a mixture of a small number of topics and that each word's creation is attributable to one of the document's topics.
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Dirichlet distribution
In probability and statistics, the Dirichlet distribution, often denoted, is a family of continuous multivariate probability distributions parametrized by a vector of positive reals. It is the multivariate generalization of the beta distribution. Dirichlet distributions are very often used as prior distributions in Bayesian statistics, and in fact the Dirichlet distribution is the conjugate prior of the categorical distribution and multinomial distribution.
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Multinomial distribution
In probability theory, the multinomial distribution is a generalization of the binomial distribution. The binomial distribution is the probability distribution of the number of "successes" in n independent Bernoulli trials, with the same probability of "success" on each trial.
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