document: Generating English summaries of time series data using the Gricean maxims We are developing technology for generating English textual summaries of time-series data , in three domains : weather forecasts , gas-turbine sensor readings , and hospital intensive care data . Our weather-forecast generator is currently operational and being used daily by a meteorological company . We generate summaries in three steps : ( a ) selecting the most important trends and patterns to communicate ; ( b ) mapping these patterns onto words and phrases ; and ( c ) generating actual texts based on these words and phrases . In this paper we focus on the first step , ( a ) , selecting the information to communicate , and describe how we perform this using modified versions of standard data analysis algorithms such as segmentation . The modifications arose out of empirical work with users and domain experts , and in fact can all be regarded as applications of the Gricean maxims of Quality , Quantity , Relevance , and Manner , which describe how a cooperative speaker should behave in order to help a hearer correctly interpret a text . The Gricean maxims are perhaps a key element of adapting data analysis algorithms for effective communication of information to human users , and should be considered by other researchers interested in communicating data to human users .
doc_bio_tags: O O O O B I I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O