Fiscal space Fiscal space Fiscal space is the flexibility of a government in its spending choices, and, more generally, to the financial well-being of a government. Peter Heller (2005) defined it “as room in a government’s budget that allows it to provide resources for a desired purpose without jeopardizing the sustainability of its financial position or the stability of the economy.” There are different exact definitions for the term, and different metrics on how to measure it. The most influential definitions of the term come from international institutions, e.g., the International Monetary Fund (IMF) and the World Bank, the United Nations agencies,
Word-sense disambiguation one typically cooks food, one can disambiguate the word bass in "I am cooking basses" (i.e., it's not a musical instrument). Supervised methods are based on the assumption that the context can provide enough evidence on its own to disambiguate words (hence, common sense and reasoning are deemed unnecessary). Probably every machine learning algorithm going has been applied to WSD, including associated techniques such as feature selection, parameter optimization, and ensemble learning. Support Vector Machines and memory-based learning have been shown to be the most successful approaches, to date, probably because they can cope with the high-dimensionality of the feature