ML Anthology

Summarizing Time-Varying Data

Sarah Boyd
AAAI 1997 pp. 824
/aaai/1997/boyd1997aaai-summarizing/

Abstract

In generating textual summaries of data, the content determination problem is even more complicated when summarizing time-varying data, such as in weather or stockmarket report generation. As well as the maxi-mum, minimum and mean, what is of interest is the behaviour of the variable over time; e.g. dramatic changes, trends and degree of variability in the data. For example, in the graph of temperature shown in Fig. 1, in addition to the max, min and mean of this data we would be interested in commenting on dramatic tem-perature changes such as the drop between the 25th and the 28th. The techniques of wavelet analysis and

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Cite

Text

Boyd. "Summarizing Time-Varying Data." AAAI Conference on Artificial Intelligence, 1997.

Markdown

[Boyd. "Summarizing Time-Varying Data." AAAI Conference on Artificial Intelligence, 1997.](https://mlanthology.org/aaai/1997/boyd1997aaai-summarizing/)

BibTeX

@inproceedings{boyd1997aaai-summarizing,
  title     = {{Summarizing Time-Varying Data}},
  author    = {Boyd, Sarah},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1997},
  pages     = {824},
  url       = {https://mlanthology.org/aaai/1997/boyd1997aaai-summarizing/}
}