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Knowledge and Information Systems
Erschienen in: Knowledge and Information Systems 2/2019

21.03.2018 | Survey Paper

Data summarization: a survey

verfasst von: Mohiuddin Ahmed

Erschienen in: Knowledge and Information Systems | Ausgabe 2/2019

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Abstract

Summarization has been proven to be a useful and effective technique supporting data analysis of large amounts of data. Knowledge discovery from data (KDD) is time consuming, and summarization is an important step to expedite KDD tasks by intelligently reducing the size of processed data. In this paper, different summarization techniques for structured and unstructured data are discussed. The key finding of this survey is that not all summarization techniques create a summary suitable for further analysis. It is highlighted that sampling techniques are a viable way of creating a summary for further knowledge discovery such as anomaly detection from summary. Also different summary evaluation metrics are discussed.
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Fußnoten
1
1 zettabyte is 1000 exabytes and 1 exabyte refers to 1 billion gigabytes.
 
2
In the field of computational linguistics, an x-gram is a contiguous sequence of x items from a given sequence of text or speech.
 
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Metadaten
Titel
Data summarization: a survey
verfasst von
Mohiuddin Ahmed
Publikationsdatum
21.03.2018
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 2/2019
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-018-1183-0

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