Data network models of burstiness

Words' Burstiness in Language Models

Good estimation of the probability of a single word is a crucial part of language modelling. It is based on raw frequency of the word in a training corpus. Such computation is a good estimation for functional words and most very frequent words, but it is a poor estimation for most content words because of words’ tendency to occur in clusters. This paper provides an analysis of words’ burstiness...

Regulation of burstiness by network-driven activation

We prove that complex networks of interactions have the capacity to regulate and buffer unpredictable fluctuations in production events. We show that non-bursty network-driven activation dynamics can effectively regulate the level of burstiness in the production of nodes, which can be enhanced or reduced. Burstiness can be induced even when the endogenous inter-event time distribution of nodes'...

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Multimedia Topic Models Considering Burstiness of Local Features

A number of studies have been conducted on topic modeling for various types of data, including text and image data. We focus particularly on the burstiness of the local features in modeling topics within video data in this paper. Burstiness is a phenomenon that is often discussed for text data. The idea is that if a word is used once in a document, it is more likely to be used again within the ...

Burstiness in Multi-tier Applications: Symptoms, Causes, and New Models

Workload flows in enterprise systems that use the multi-tier paradigm are often characterized as bursty, i.e., exhibit a form of temporal dependence. Burstiness often results in dramatic degradation of the perceived user performance, which is extremely difficult to capture with existing capacity planning models. The main reason behind this deficiency of traditional capacity planning models is t...