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Generating Weather Forecast Texts with Case based Reasoning

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International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 45 - Number 10
Year of Publication: 2012
Authors:
Ibrahim Adeyanju
10.5120/6819-9176

Ibrahim Adeyanju. Article: Generating Weather Forecast Texts with Case based Reasoning. International Journal of Computer Applications 45(10):35-40, May 2012. Full text available. BibTeX

@article{key:article,
	author = {Ibrahim Adeyanju},
	title = {Article: Generating Weather Forecast Texts with Case based Reasoning},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {45},
	number = {10},
	pages = {35-40},
	month = {May},
	note = {Full text available}
}

Abstract

Several techniques have been used to generate weather forecast texts. In this paper, case based reasoning (CBR) is proposed for weather forecast text generation because similar weather conditions occur over time and should have similar forecast texts. CBR-METEO, a system for generating weather forecast texts was developed using a generic framework (jCOLIBRI) which provides modules for the standard components of the CBR architecture. The advantage in a CBR approach is that systems can be built in minimal time with far less human effort after initial consultation with experts. The approach depends heavily on the goodness of the retrieval and revision components of the CBR process. We evaluated CBR-METEO with NIST, an automated metric which has been shown to correlate well with human judgements for this domain. The system shows comparable performance with other NLG systems that perform the same task.

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